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Recent developments in emissions regulations are pushing Non-Road Mobile Machineries manufacturers towards the adoption of more efficient solutions to reduce the amount of pollutants per unit of work performed. Electrification can be a reasonable alternative to traditional powertrain to achieve this goal. The higher complexity of working machines architectures requires, now more than ever, better design and testing methodologies to better integrate electric systems into mechanical and hydraulic layouts. In this work, the attention focused on the use of a Hardware in the Loop (HIL) approach to test performance of an energy management strategy (called load observer) developed specifically for an orchard tractor starting from field characterization. The HIL bench was designed to replicate a scaled architecture of a parallel hybrid electric tractor at mechanical and electrical level. The vehicle behavior was simulated with a personal computer connected on the CAN BUS network designed for the HIL system. Several tasks were simulated starting from data gathered during field measurements of a daily use of the machine. Results showed good performance in terms of load split between the two power sources and stability of the speed control although the variability of the applied load.

Long robotic arms are useful for many applications such as nuclear plant decommissioning, inspection, and firefighting. A major problem for designing and operating long robotic arms is that even small end effector reaction forces and arm gravity can result in large loads on proximal arm joints because of long moment arms. To solve that problem, previous researches focus on specifically designed long arms with certain compensation mechanisms. However, those specialized arm designs are difficult to be applied to existing long robotic arms and to be customized for different missions. To overcome those two drawbacks, we recently proposed a watch-like thrust-generating modular device, called flying watch, with the following two major advantages. Firstly, flying watch can be attached to different kinds of existing long robotic arms and generate thrusts to enhance arm strength. And we have proposed a thrust planning method for flying watch in our previous work. Secondly, since different flying watch attachment allocations can enhance the same robotic arm in different ways, flying watch attachment allocations can be customized to meet the needs of a specific mission. However, up to now, customizing flying watch attachment allocations to different missions is still based on human experience and there is no clear performance metric and automated design method for flying watch attachment allocation. To facilitate mission-dependent long arm enhancement, in this paper, we first propose a novel performance metric, called thrust drivability, which measures the ability of a flying watch attachment allocation to counteract unexpected end effector reaction forces. Then based on thrust drivability, we propose an automated design method, called Allocation Optimization based on Weighted Situations (AOWS), for generating mission-dependent flying watch attachment allocations counteracting both unexpected and known external forces. Simulations show that AOWS based allocation designs can counteract both known and unexpected external forces much better than human-experience-based allocation designs.

This paper presents an EKF-based self-attitude estimation with a DNN (deep neural network) learning landscape information. The method integrates gyroscopic angular velocity and DNN inference in the EKF. The DNN predicts a gravity vector in a camera frame. The input of the network is a camera image, the outputs are a mean vector and a covariance matrix of the gravity. It is trained and validated with a dataset of images and corresponded gravity vectors. The dataset is collected in a flight simulator because we can easily obtain various gravity vectors, although the method is not only for UAVs. Using a simulator breaks the limitation of amount of collecting data with ground truth. The validation shows the network can predict the gravity vector from only a single shot image. It also shows that the covariance matrix expresses the uncertainty of the inference. The covariance matrix is used for integrating the inference in the EKF. Flight data of a drone is also recorded in the simulator, and the EKF-based method is tested with it. It shows the method suppresses accumulative error by integrating the network outputs.

Few physical models of oral and laryngeal systems for human speech movement exist for computer or mechanical simulators. In particular, a robot tongue mechanism that fully reproduces the deformation motion of the human tongue is lacking. The human tongue is an aggregate of muscles that is devoid of a skeleton. It possesses only a small hyoid. A mechanism that can drive and control the deformation of a soft body, such as the human tongue, along multiple degrees of freedom has not been realized to date. To solve this problem, a wire-pulling mechanism with embedded soft tubes is proposed. Using this mechanism, a flexible tongue that can be deformed along multiple degrees of freedom without breaking the wire is achieved. A prototype planar mechanism with two degrees of freedom that is capable of contraction and bending was fabricated. A deformation model that assumes a piecewise constant curvature (PCC) was formulated. Deformation tests confirmed that the prototype is capable of contraction and bending movements that are consistent with those of the model. Variations in the error with respect to the hardness of the deformable part are discussed, and the limits of the deformation model based on the PCC assumption are presented.

Direct Yaw Moment Control (DYC) is an effective way to alter the behaviour of electric cars with independent drives. Controlling the torque applied to each wheel can improve the handling performance of a vehicle making it safer and faster on a race track. The state-of-the-art literature covers the comparison of various controllers (PID, LPV, LQR, SMC, etc.) using ISO manoeuvres. However, a more advanced comparison of the important characteristics of the controllers’ performance is lacking, such as the robustness of the controllers under changes in the vehicle model, steering behaviour, use of the friction circle, and, ultimately, lap time on a track. In this study, we have compared the controllers according to some of the aforementioned parameters on a modelled race car. Interestingly, best lap times are not provided by perfect neutral or close-to-neutral behaviour of the vehicle, but rather by allowing certain deviations from the target yaw rate. In addition, a modified Proportional Integral Derivative (PID) controller showed that its performance is comparable to other more complex control techniques such as Model Predictive Control (MPC).

Probabilistic localization based on Bayesian theory has been researched as a sensor fusion method to improve the robustness of localization. Pieces of position information, generated by sensors’ observation models with consideration for noises, are fused according to Bayesian theory. However, having large noises not considered in their observation models, the sensors output erroneous position information; thus, the fusion result has a significant error, even when the other sensors output correct ones. In this research, we have proposed a sensor fusion system with a relative correlation checking test to realize robust localization. Pieces of erroneous position information, biased against others and having a negative correlation with others, are detected and excluded in our proposed system by checking their correlation between all of them. The purpose of this paper is to evaluate the robustness of our fusion system by conducting recursive localization experiments in various environments.

Autonomous robots are expected to replace dangerous, dirty, and demanding (3D) jobs. At a theme park, surveillance, cleaning, and guiding tasks can be regarded as 3D jobs. The present paper attempts to develop an autonomous tour guide robot system and co-experience system at a large theme park. For realizing such autonomous service robots used in our daily environment, localization is one of the most important and fundamental functions. A number of localization techniques, including simultaneous localization and mapping, have been proposed. Although a global navigation satellite system (GNSS) is most commonly used in outdoor environments, its accuracy is approximately 10 m, which is inadequate for navigation of an autonomous service robot. Therefore, a GNSS is usually used together with other localization techniques, such as map matching or camera-based localization. In the present study, we adopt the quasi-zenith satellite system (QZSS), which became available in and around Japan in November 2018, for the localization of an autonomous service robot. The QZSS provides high-accuracy position information using quasi-zenith satellites (QZSs) and has a localization error of less than 10 centimeters. In the present paper, we compare the positioning performance of the QZSS and the real-time kinematic GPS and verify the stability and the accuracy of the QZSS in an outdoor environment. In addition, we introduce a tour guide robot system using the QZSS and present the results of a guided tour experiment in a theme park. On the other hand, based on the tour guide system, we also develop a co-experience robot system in a theme park, which realizes the sharing of experiences using an immersive VR display and the 5th-generation mobile communication system (5G). The robot is equipped with a 360-degree video camera and real-time 4K video is transmitted to a remote operator using the large communication capacity of the 5G network. The experimental results at a theme park showed that the guided tour experiment was successful and that the co-experience system allowed sharing of the experience with high immersion by a remote operator.

The ever-increasing demand for transportation of people and goods as well as the massive accumulation of population in urban centers have increased the need for appropriate infrastructure and system development in order to efficiently manage the constantly increasing and diverse traffic flows. Moreover, given the rapid growth and the evolution of Information and Communication Technologies (ICT), the development of intelligent traffic management systems that go beyond traditional approaches is now more feasible than ever. Nowadays, highways often have sensors installed across their range that collect data such as speed, density, direction and so on. In addition, the rapid evolution of vehicles with installed computer systems and sensors on board, provides a very large amount of data, ranging from very simple features such as speed, acceleration, etc. to very complex data like the driver&rsquo, s situation and driving behavior. However, these data alone and without any further processing, cannot solve the congestion problem. Therefore, the development of complex computational methods and algorithms underpins the chance to process these data in a fast and reliable way. The purpose of this paper is to present a traffic control ramp metering (RM) method based on machine learning and to study its impact on a selected highway segment.

Graph-based design languages have received increasing attention in the research community, because they offer a promising approach to address several major issues in engineering, e.g., the frequent manual data transfer between computer-aided design (CAD) and computer-aided engineering (CAE) systems. Currently, these issues prevent the realization of machine executable digital design processes of complex systems such as vehicles. Promising scenarios for urban transportation include an interconnection of mass transportation systems such as buses and subways with individual vehicles for the so-called &ldquo, last mile&rdquo, transport. For several reasons, these vehicles should be as small and light as possible. A considerable reduction in weight and size can be achieved, if such vehicles are tailored to the individual size, weight and proportion of the individual user. However, tailoring vehicles for the individual characteristics of each user go beyond a simple building set and require a continuous digital design process. Consequently, the topic of this paper is a digital design process of a self-balanced scooter, which can be used as an individual last-mile means of transport. This process is based on graph-based design languages, because in these languages, a digital system model is generated, which contains all relevant information about a design and can be fed into any simulation tool which is needed to evaluate the impact of a possible design variation on the resulting product performance. As this process can be automated by digital compilers, it is possible to perform systematic design variations for an almost infinite amount of parameters and topological variants. Consequently, these kinds of graph-based languages are a powerful means to generate viable design alternatives and thus permit fast evaluations. The paper demonstrates the design process, focusing on the drive system of the respective balanced two-wheel scooter and highlights the advantages (data integration and possibility for machine execution).

The paper is devoted to the measurement and to the processing of load spectra of forces and moments acting at the wheel hub of a motorcycle. Smart wheels (SWs) have been specifically developed for the scope. Throughout the paper, the extreme case of a race motorcycle is considered. Accurate load spectra were measured in two race circuits. Standardized load spectra are derived by processing measured data. A way to easily generalize the measured load spectra is proposed for the first time for motorcycles. Several loading conditions, related to the motorcycle straight line motion, cornering, curb hit and gear shift, are identified and extracted from the experimental measures. For each loading condition, by means of simple semi-analytical models (SAMs), a relationship is found between the vertical force on the wheel, the tilt angle of the motorcycle and the remaining forces and moments acting at the wheel hub. Such relationships are nothing else than the standardized load spectra. Additionally, a simple and efficient method based on smart wheels for real-time structural monitoring is proposed. Standardized load spectra prove to provide consistent results even when compared to real-time structural monitoring data. By means of the presented smart wheels, advanced lightweight motorcycle construction is enabled by derivation of standardized load spectra or real time estimation of the damage of structural components.

Driving simulators are widely used for understanding human&ndash, machine interaction, driver behavior and in driver training. The effectiveness of simulators in this process depends largely on their ability to generate realistic motion cues. Though the conventional filter-based motion-cueing strategies have provided reasonable results, these methods suffer from poor workspace management. To address this issue, linear MPC-based strategies have been applied in the past. However, since the kinematics of the motion platform itself is nonlinear and the required motion varies with the driving conditions, this approach tends to produce sub-optimal results. This paper presents a nonlinear MPC-based algorithm which incorporates the nonlinear kinematics of the Stewart platform within the MPC algorithm in order to increase the cueing fidelity and use maximum workspace. Furthermore, adaptive weights-based tuning is used to smooth the movement of the platform towards its physical limits. Full-track simulations were carried out and performance indicators were defined to objectively compare the response of the proposed algorithm with classical washout filter and linear MPC-based algorithms. The results indicate a better reference tracking with lower root mean square error and higher shape correlation for the proposed algorithm. Lastly, the effect of the adaptive weights-based tuning was also observed in the form of smoother actuator movements and better workspace use.

Designing new mechatronic systems for vehicle applications is a complex and time-consuming process. The increasing computational power allows us to generate automatically novel and new mechatronic discrete-topology concepts in an efficient manner. Using state-of-the-art computational design synthesis techniques assures that the complete search space, given a finite set of system elements, is processed to find all feasible topologies. The topology generation is done by converting the design synthesis problem into a constraint satisfaction problem. Accordingly, this mathematical problem is solved by assigning the presence of components and connections to variables, whereby a set of mathematical constraints need to be satisfied. These constraints capture, in essence, formalized engineering knowledge. After solving this problem, the results are post-processed to discard redundant topologies due to isomorphism. In this paper, a newly developed software application with automated constraint generation is presented that facilitates the topology generation with multiple system levels in a loop. The scalability of the problem and the different levels of expressiveness are analyzed, and the influence of the abstraction level choice on the search space is discussed. Finally, a relevant mechatronic design study from the automotive engineering field is discussed concerning the topology synthesis of alternative electro-hydraulic actuation systems being part of new continuously variable transmission topologies, thus showing its applicability.

Planetary exploration rovers have required a high traveling performance to overcome obstacles such as loose soil and rocks. Push-pull locomotion rovers is a unique scheme, like an inchworm, and it has high traveling performance on loose soil. Push-pull locomotion uses the resistance force by keeping a locked-wheel related to the ground, whereas the conventional rotational traveling uses the shear force from loose soil. The locked-wheel is a key factor for traveling in the push-pull scheme. Understanding the sinking behavior and its resistance force is useful information for estimating the rover’s performance. Previous studies have reported the soil motion under the locked-wheel, the traction, and the traveling behavior of the rover. These studies were, however, limited to the investigation of the resistance force and amount of sinkage for the particular condition depending on the rover. Additionally, the locked-wheel sinks into the soil until it obtains the required force for supporting the other wheels’ motion. How the amount of sinkage and resistance forces are generated at different wheel sizes and mass of an individual wheel has remained unclear, and its estimation method hasn’t existed. This study, therefore, addresses the relationship between the sinkage and its resistance force, and we analyze and consider this relationship via the towing experiment and theoretical consideration. The results revealed that the sinkage reached a steady-state value and depended on the contact area and mass of each wheel, and the maximum resistance force also depends on this sinkage. Additionally, the estimation model did not capture the same trend as the experimental results when the wheel width changed, whereas, the model captured a relatively the same trend as the experimental result when the wheel mass and diameter changed.

Automatic analysis of our daily lives and activities through a first-person lifelog camera provides us with opportunities to improve our life rhythms or to support our limited visual memories. Notably, to express the visual experiences, the task of generating captions from first-person lifelog images has been actively studied in recent years. First-person images involve scenes approximating what users actually see; therein, the visual cues are not enough to express the user’s context since the images are limited by his/her intention. Our challenge is to generate lifelog captions using a meta-perspective called “fourth-person vision”. The “fourth-person vision” is a novel concept which complementary exploits the visual information from the first-, second-, and third-person perspectives. First, we assume human–robot symbiotic scenarios that provide a second-person perspective from the camera mounted on the robot and a third-person perspective from the camera fixed in the symbiotic room. To validate our approach in this scenario, we collect perspective-aware lifelog videos and corresponding caption annotations. Subsequently, we propose a multi-perspective image captioning model composed of an image-wise salient region encoder, an attention module that adaptively fuses the salient regions, and a caption decoder that generates scene descriptions. We demonstrate that our proposed model based on the fourth-person concept can greatly improve the captioning performance against single- and double-perspective models.

This paper describes development of a mobile robot using semicircular wheels on uneven terrain. It performs the crawl gait on flat ground without changing potential energy and the butterfly gait to climb over debris. We also used crawl gait to perform turning motion. The butterfly gait is used to climb over high steps. Turning motion is achieved not only by creating a difference in angular velocity between the wheels on both sides, but also by keeping the crawl gait. We achieved continuous movement from turning motion to pivot turning. We conducted an experiment on the movement and turning motion on flat ground using crawl gait.

Teleoperated robots are expected to perform tasks in extreme environments such as disaster sites. However, only few teleoperated robots are used for this purpose because their usability is poor compared to human skill in such tasks. Further, the use of human–machine interfaces used by teleoperated robots is in itself a human skill. In this study, we compare the skills of firefighters (experts) when using teleoperated robots and that of firefighters (novice) and analyze the results. Firefighters gain technical skills required for fighting fires from practical experiences; in comparison, novice firefighters have trouble acquiring these skills. We conducted a comparative experiment of the reconnaissance skills of firefighters in which ten firefighters (five novices and five experts) reconnoiter two simulated fire sites (one in a residential area and the other in a commercial facility area) with a teleoperated robot. The experimental results indicated that experts were more multifaceted in their evaluation of reconnaissance areas as compared to novices.

In this paper, a navigation and environment mapping method is presented for small exploration robots that use hopping motion. While previous research about hopping rovers mostly focuses on mobility and mechanical design, the motivation for the proposed method is to provide a fully autonomous navigation system using only a monocular camera. The method accurately estimates the hopping distance and reconstruct the 3D environment using Structure from Motion, proving that a monocular system is not only feasible, but accurate and robust at the same time. The relative scale problem of the reconstructed scene and trajectory is solved by the known gravity and parabolic motion constraints. After each hop, the error in landing position is corrected by a modified Iterative Closest Point algorithm with non-overlapping part elimination. The environmental point cloud is projected onto a 2D image, that is used to find the most suitable landing position for the next hop using protrusion based obstacle detection, and navigate the robot towards the goal direction. Both virtual environment simulations and real experiments confirm the feasibility and highlight the advantages of the presented method.

The currently available exoskeleton for assisting the paraplegic patient in walking usually adapts a pre-programmed gait that involves the patient following an exoskeleton lead. The system allows the patient to hold a pair of canes in order to keep balance, and does not contribute to keeping balance without the patient’s action. This paper proposes an algorithm based on the zero moment point (ZMP) to modify the gait generated through human walking synergy for paraplegic patients who make use of the exoskeleton system and hold their canes. The proposed ZMP will enable the paraplegic patient to keep balance during walking and also reduce the burden in maintaining balance. First, a pair of cane is used as an interface to control the user’s walking and then, the synergy between legs and canes is used to synchronize the user’s walking intention during the exoskeleton movement. The walking synergy is extracted from the able-bodied subject walking with a pair of canes and analyzed using principal component analysis (PCA). In order to improve the walking stability, the hip joint angle on stance leg during walking was modified based on ZMP. Furthermore, a nonlinear inverted pendulum (NIP) model was utilized in order to generate a gait with a fully stretched knee joint angle that is similar to human gait. The proposed method was verified via the Gazebo simulation using a walking robot to simulate a patient wearing an exoskeleton. The experiment results show that the walking stability was highly improved after gait modification.

In this paper, we propose a wearable tactile sensor for measuring the shape of micro-undulations on a hard surface. The proposed sensor has two layers. The inner one is a thin rubber layer into which a strain gauge is embedded that is formed around a user’s finger. The outer layer is a flexible structure that consists of numerous pins on a flexible sheet. The shape of micro-undulations on an object surface can be measured when a user wearing the sensor traces the surface. The results of an experiment, in which we compare the cases with and without the flexible structure of the sensor, show that our proposed sensor is sufficiently accurate to measure the shape of micro-undulations due to its flexible structure, which contributes significantly to improving its signal-to-noise ratio.

One of the main challenges for the elderly is insufficient lower limb strength during sit-to-stand movement, which may be improved by supporting the joint externally. Existing lower extremity exoskeletons use perfect revolute joints as knee joints, which do not match with human joint biomechanics. They also require a complex control system to produce the required torque at the corresponding joint angle. In this study, a knee support device using four-bar joint mechanism and hydraulic artificial muscle (HAM) was designed. A previously proposed four-bar linkage joint was modified to accommodate the HAM. In addition, the Angled Bar was proposed to exploit HAM’s force-contraction relationship to generate the desired torque at the corresponding angle only by applying constant hydraulic pressure without the use of a complex control system. The device was able to generate a maximum output of 126.55 Nm torque at 100$$^{\circ }$$∘ knee joint angle during loading and 70.69 Nm torque at 100$$^{\circ }$$∘ during unloading at 3 MPa pressure. The root-mean-square error of the knee extension torque curve was 13.01 Nm. Experiment with a healthy participant showed significant reduction in muscle activity with the assist from the device. The maximum processed EMG signal with and without assist were 52.10 and 20.93 $${\upmu \mathrm{V}}$$μV, respectively.

As the geriatric population expands, caregivers require more accurate training to handle and care for the elderly. However, students lack methods for acquiring the necessary skill and experience, as well as sufficient opportunities to practice on real human beings. To investigate the necessity and feasibility of care training assistant robots in care education, we developed a simulated robot as a shoulder complex joint with multi-DOF. In this study, five experts with years of experience in elderly care participated in the data-acquisition process, to acquire information on aspects such as the glenohumeral angle, as well as the sterno-clavicular joint and its torque. The experts performed three types of range-of-motion exercises: (i) elevation–depression of sterno-clavicular joint; (ii) extension and flexion of glenohumeral joint; (iii) lateral and medial rotation of glenohumeral joint. The experimental results showed that the quantitative results for all the exercises were significantly different between the experts. Moreover, we observed that even experienced professionals need consistent care education based on quantitative data and feedback. Thus, we confirmed the necessity and feasibility of the care training assistant robot for improving the skills required for elderly care.

In this paper, a novel visual-tactile sensor is proposed; additionally, an object manipulation method for a multi-fingered robotic hand grasping an object is proposed by detecting a contact position using the visual-tactile sensor. The visual-tactile sensor is composed of a hemispheric fingertip made of soft silicone with a hollow interior and a general USB camera located inside the fingertip to detect the displacement of the many point markers embedded in the silicone. The deformation of each point marker due to a contact force is measured, and a contact position is estimated reliably through a novel method of creating virtual points to determine the point clouds. The aim is to demonstrate both the estimation performance of the new visual-tactile sensor and its usefulness in a grasping and manipulation task. By using the contact position obtained from the proposed sensor and the position of each fingertip obtained from kinematics, the position and orientation of a grasped object are estimated and controlled. The effectiveness of the method is illustrated through numerical simulation and its practical use is demonstrated through grasping and manipulating experiments.

This paper describes a vacuum suction-type end effector for depalletizing robots in distribution centers. The developed end effector has multiple suction pad units to which a bellows pneumatic actuator is applied as the support mechanism. Load-bearing capacity is improved due to a high-strength wire provided inside the bellows, and the contraction force is improved due to ring members placed inside of the ridges of the rubber bellows. The developed end effector is attached to the arm of a linear motion-type depalletizing robot, and its real-world performance is verified. Verification results confirm that the suction pad units tolerate cardboard box inclination and differences in box height by a simple lowering motion of the arm, and multiple cardboard boxes can be simultaneously unloaded. Moreover, as compared with conventional end effectors, the developed end effector achieves large expansion and contraction in a thin structure. The developed end effector is expected to broaden applications for depalletizing robots.

The mechanical properties of cells, such as leukocytes, in a diseased state differ from those of healthy cells, typically due to their microstructure. The deformability of the cells through a constrictive area is analyzed by the applied stress to the cell. This study investigates the relationship between the sample flow speed and distribution of captured leukocytes based on the cell deformability using a microfluidic device. The device comprises of microfilters that serve as the filtration mechanism. The microfilter gap size gradually decreases from 15 to 3 µm to facilitate the deformability-based separation. Leukocytes have various sizes; hence, they can be separated by microfilters directly from whole blood samples without any cell clogging, and they do not require sample pre-processing such as centrifugation or red blood cell lysis. The distribution of leukocytes captured by the microfilters with respect to the sample flow speed can be analyzed; at higher sample flow speeds of 6 µL/min, small leukocytes with a size of 7 µm could not be captured and they passed through the smallest microfilter gap size of 3 µm. For smaller leukocytes, such as lymphocytes, the distributions are mainly at gap sizes of 4 µm to 8 µm, with most of the lymphocytes captured at the 6 µm microfilter gap size. We conclude that the distribution of the cells captured during the filtration varies depending on the microfilter gap sizes, applied sample flow speed, cell sizes, and the ability of the cells to deform. The deformability imaging profiles of the sample could be developed from the images of the cell distribution, which might be useful for preliminary screening in the clinical applications. This work presents the development of a simple device for the study of cell deformability as the results provide a biophysical marker in high throughput and bulk sample analyses.

Spatial change detection is a fundamental technique for finding the differences between two or more pieces of geometrical information. This technique is critical in some robotic applications, such as search and rescue, security, and surveillance. In these applications, it is desirable to find the differences quickly and robustly. The present paper proposes a fast and robust spatial change detection technique for a mobile robot using an on-board range sensors and a highly precise 3D map created by a 3D laser scanner. This technique first converts point clouds in a map and measured data to grid data (ND voxels) using normal distributions transform. The voxels in the map and the measured data are then compared according to the features of the ND voxels. Three techniques are introduced to make the proposed system robust for noise, that is, classification of point distribution, overlapping of voxels, and voting using consecutive sensing. The present paper shows the results of indoor and outdoor experiments using an RGB-D camera and an omni-directional laser scanner mounted on a mobile robot to confirm the performance of the proposed technique.

Brain damage due to stroke often leaves survivors with lateral functional motor deficits. Bimanual rehabilitation of the paretic arm is an active field of research aimed at restoring normal functionality by making use of the complex neural bindings that exist between the arms. In search of an effective rehabilitation method, we introduced a group of post-stroke rehabilitation patients to a set of bimanual motion tasks with inter-manual coupling and phasing. The surface EMG profiles of the patients were compared in order to understand the effect of the motion conditions. The paretic arms of the patients were more strongly affected by the task conditions compared with the non-paretic arms. These results suggest that in-phase motion may activate neural circuits that trigger recovery. Coupling also had an effect on behavior, but the response of patients was divided between those whom coupling helped or hindered.

Slippage occurrence has an important roll in stable and robust object grasping and manipulation. However, in majority of prior research on soft finger manipulation, presence of the slippage between fingers and objects has been ignored. In this paper which is a continuation of our prior work, a revised and more general method for dynamic modeling of planar slippage is presented using the concept of friction limit surface. Friction limit surface is utilized to relate contact sliding motions to contact frictional force and moment in a planar contact. In this method, different states of planar contact are replaced with a second-order differential equation. As an example of the proposed method application, dynamic modeling and slippage analysis of object manipulation on a horizontal plane using a three-link soft finger is studied. Then, a controller is designed to reduce and remove the undesired slippage which occurs between the soft finger and object and simultaneously move the object on a predefined desired path. Numerical simulations reveal the acceptable performance of the proposed method and the designed controller.

This paper presents fabrication and actuation methods for a soft microrobot with a hybrid structure composed of soft microactuators and a rigid supporting body. This hybrid structure enables actuation of the microrobot with independent driving of multiple actuators to provide complex movement like that of living microorganisms. We use the temperature-responsive hydrogel poly(N-isopropylacrylamide) (PNIPAAm) as a soft microactuator. PNIPAAm swells with water at low temperature but shrinks at high temperature. This volume change thus allows PNIPAAm to be used as an actuator by controlling its temperature. We successfully fabricated the microrobot with its soft-rigid hybrid structure composed of PNIPAAm and rigid photoresist using a multilayered microfabrication process. In addition, we used a sacrificial layer process to release the fabricated microrobot from the substrate to allow it to move freely. To actuate the microrobot, we mixed PNIPAAm with graphene, which has a high photothermal conversion efficiency. The temperature of the soft actuator when mixed with graphene can be increased by irradiating it with light. Therefore, actuation of the microrobot is achieved by sequentially irradiating the microactuators with focused light. We present the fabrication, release and partial actuation of the microrobot to demonstrate the feasibility of the proposed microrobot with the soft-rigid hybrid structure in this paper.

Breast cancer diagnosis has been mostly accomplished through imaging. These methods have great advantages in being able to detect the presence and location of breast cancer. However, it is difficult to distinguish between a benign and malignant tumor located in a deep position because both tumor types look similar. In this paper, tissue including the tumor from skin was vibrated using a compression cylinder, to analyze the frequency difference for distinguishing tissue type. Before distinguishing between a benign and malignant tumor, it is necessary to validate that the difference between normal tissue and tumor can be distinguished. The objective of the study is to validate the feasibility to emphasize the frequency differences in a 10.0 mm or greater deep tumors during vibration by pushing a cylinder towards the deep tumor. A phantom model and finite element analysis model were constructed to simulate the breast. In the experiment, air was injected into the phantom and the displacement was measured. The frequency response for distinction of tissue types was analyzed and it was found that the displacement difference rate was over 50% at a frequency of 130 Hz when the cylinder was pushed into the sample as opposed to when not pushed in. Changes in displacement were measured according to the distance between the tumor and vibration point using finite element analysis. When the measurement and vibration points were on the center of the tumor, the difference in the resonance point was at its largest (5.5 Hz). Results show that the position of a tumor could be easily and rapidly detected by vibrations from a cylinder pushed into the diagnostic site.

One of the recommended post-stroke gait rehabilitation treatments is the use of an ankle–foot orthosis. In clinical practice, it is important to adjust the torque of the ankle–foot orthosis assistance to suit each patient’s body function and gait ability. The present study aimed to investigate the effect of changing the plantar flexion resistance of the ankle–foot orthosis on the post-stroke gait kinematics and kinetics during the early stance phase using a musculoskeletal model and an ankle–foot orthosis model. The subject was a male with post-stroke left hemiplegia who could walk independently without an ankle–foot orthosis and/or cane. The subject walked at a self-selected speed under the no ankle–foot orthosis condition and three ankle–foot orthosis conditions, each with a different plantar flexion resistive torque. A motion analysis system was used to measure the following spatiotemporal parameters: gait speed, step length, cadence, and step length ratio. In addition, the ankle angle of the paretic side, ankle torque of the paretic side, and plantar flexion resistance torque of the ankle–foot orthosis were calculated using a musculoskeletal model and an ankle–foot orthosis model. The results showed that the gait speed and step length ratio of all ankle–foot orthosis conditions were improved compared with the no ankle–foot orthosis condition. In particular, the condition with the smallest torque was the most symmetric of the four walking conditions. The condition with the smallest torque also resulted in the greatest increase in the dorsiflexion angle of the paretic side at heel contact. The internal dorsiflexion torque was most increased in the ankle–foot orthosis condition with the smallest torque for this subject. The simulation of the post-stroke gait in the present study contributes to the development of more effective gait rehabilitation treatment methods using an ankle–foot orthosis.

A long-reach robotic arm is useful for applications such as nuclear plant decommissioning, inspection, and firefighting. However, for such arms, a small external reaction force can result in large loads on proximal arm actuators because of long moment arms. This problem was previously solved by specialized arm designs that compensate external reaction forces. However, these arm designs are hard to be applied to other arms or customized to different missions. To overcome these difficulties, in this paper, we propose a modular thrust generating concept inspired by wristwatch designs, called flying watch, which can be attached to a robotic arm with mission-dependent attachment styles (attachment positions and orientations) and cooperate with actuators to enhance arm strength. We first introduce flying watch concept, design, and dynamics. Then we propose two levels of watch-actuator cooperation in quasistatic situations by introducing a problem called Watch Actuator Cooperation for Arm Enhancement (WACAE) and providing an example solution. The first level of cooperation is only watches adapt their thrusts to minimize actuator loads, which is generally applicable to varieties of arms. The second level cooperation is that not only do the watches adapt their thrusts but also the actuators cooperatively position the watches to optimal positions and orientations to counteract external reaction forces, which is suitable for redundant arms and can counteract external reaction forces more effectively. Finally, we present simulations to verify that flying watches can significantly reduce actuator loads using both levels of watch-actuator cooperation (the first level by 36.9% and the second level by 43.7%).

Generation of stable and realistic haptic feedback during mid-air gesture interactions have recently garnered significant research interest. However, the limitations of the sensing technologies such as unstable tracking, range limitations, nonuniform sampling duration, self occlusions, and motion recognition faults significantly distort motion based haptic feedback to a large extent. In this paper, we propose and implement a hidden Markov model (HMM)-based motion synthesis method to generate stable concurrent and terminal vibrotactile feedback. The system tracks human gestures during interaction and recreates smooth, synchronized motion data from detected HMM states. Four gestures—tapping, three-fingered zooming, vertical dragging, and horizontal dragging—were used in the study to evaluate the performance of the motion synthesis methodology. The reference motion curves and corresponding primitive motion elements to be synthesized for each gesture were obtained from multiple subjects at different interaction speeds by using a stable motion tracking sensor. Both objective and subjective evaluations were conducted to evaluate the performance of the motion synthesis model in controlling both concurrent and terminal vibrotactile feedback. Objective evaluation shows that synthesized motion data had a high correlation for shape and end-timings with the reference motion data compared to measured and moving average filtered data. The mean $$R^{2}$$ values for synthesized motion data was always greater than 0.7 even under unstable tracking conditions. The experimental results of subjective evaluation from nine subjects showed significant improvement in perceived synchronization of vibrotactile feedback based on synthesized motion.

Laparoscopic surgery, which is also called minimally invasive surgery, is a surgical technique that is associated with accelerated post-operative recovery. However, it can only be performed by surgeons possessing advanced surgical skills. One of the main challenges in laparoscopic surgery is the restriction of the free motion of forceps because of the limited degrees of freedom imposed by the trocar. Recently, to overcome this problem, many master–slave manipulators with articulated forceps have been used in laparoscopic surgery. The wrist mechanism of the articulated forceps affects the controllability and range of motion of the slave manipulator in the abdominal cavity of a patient. Therefore, improvement of the wrist mechanism of the articulated forceps is important for robot-assisted laparoscopic surgery. This study proposes a new wrist mechanism for using articulated forceps in laparoscopic surgery. The degrees of freedom of the proposed design are provided by motor-driven or manually driven axes employing various wires and pulleys (pitch, yaw, and gripper axes). The kinematic model of this mechanism is decoupled between the pitch axis and yaw axis by a very simple mechanism using arc-shaped guides and wire guide holes. The arc-shaped guides minimize the wire path length error of the yaw and gripper axis wire resulting from the motion of the pitch axis. The optimized position of the arc-shaped guides is decided by the minimal root-mean-square value of the wire path length error. The proposed wrist mechanism has only half the number of parts as compared to the previously developed robotic forceps for clinical use. Furthermore, the effectiveness of the proposed mechanism was demonstrated on a prototype model with a maximum outer diameter of 7.5 mm. Conversely, the disadvantages of the proposed mechanism lie in the transmission mechanism efficiency and no-load input torque.

Innovative activity of enterprises in Poland is mostly generated by European funds that concern boosting European regions based on its significant resources and new technologies. Polish enterprises development within innovations is based mainly on accumulating new products and new technologies that improve organization and increase sale of products and services. Papers presents research findings that concern problems resulting from the innovations implementing in Polish enterprises comparing with European results. There is presented European Innovation Index providing a comparative assessment of the innovation performance at the country level of the EU Member States and the Regional Innovation Scoreboard (RIS) that presents results of innovative activity in Polish and European enterprises including regional data from the Community Innovation Survey (CIS).

Electric cars represent a promising energy-and carbon-efficient alternative to internal combustion engine cars. However, as mobility behaviour is highly habitual, convincing people to switch from conventional cars to electric is challenging. In the following research, which was carried out in the past years in Slovenia, an attempt was made to determine what influences people’s buying habits and what would motivate them to buy an electric car. It appeared that the most relevant factor for not purchasing electric cars is, firstly, its overall too high price, and, secondly, short driving ranges. Different studies, as well as the results of the following research have revealed that there is no single measure which would dramatically increase the demand for electric cars. The solution is to combine different measures or strategies like Top – Down and Bottom – Up, where both the government and car industry should come across.

Paper describes the procedure for developing academic programs which are properly aligned to the requirements of the knowledge-based economy. The paper also addresses the continuous quality improvement (CQI) process with the CQI loop closing on the program level and the course level. This process is needed to make continuous adjustments to an academic program, so that the program is always aligned to the constantly-changing needs of the economy. Paper also discusses the system of mutual dependency between the academic program and external partnership like local industry, secondary schools, local government, local community, regional business incubator center, other educational institutions, alumni and industrial advisory council. The ongoing collaboration with external partners allows the program to prosper and grow.

The popularity of visual management in the lean concept is caused by the possibility to apply it in solving different kind of issues related to reduce waste or process planning. The adaptations of VSM is focused on stream flow, identifying waiting and productive times in accordance to material and information flow. In this paper five basic areas of value stream flow management have been presented and characterized. Discussion under the 5 areas on the VSM process included identifying the dominant stream in the area and the range of factors affecting the flow of the stream. Based on an observation of processes in the manufacturing industry and a literature review, the graphic model of mutual cooperation between value stream areas (1-5) has been presented.

In the work of a dentist there are many factors that affect the occupational risk. They cover the area of the human factor, work organization and technical area. The latter often determines the safety and ergonomics of the workplace. The purpose of this article is to identify occupational hazards in the work of a dentist, with particular emphasis on the technical area. The method used in the article is a survey supported by observation with elements of a direct interview. The research tool used in the article is a questionnaire in the form of a checklist.

The article discusses the results of a study investigating the effect of the number of fine non-metallic inclusions (up to 2 μm in size) on the fatigue strength of structural steel during rotary bending. The study was performed on 7 heats produced in an industrial plant. Fourteen heats were produced in a 100 ton oxygen converter. All heats were subjected to vacuum circulation degassing. Steel sections with a diameter of 18 mm were hardened and tempered at a temperature of 200, 300, 400, 500 and 600°C. The experimental variants were compared in view of the applied melting technology and heat treatment options. The heat treatments were selected to produce heats with different microstructure of steel, from hard microstructure of tempered martensite, through sorbitol to the ductile microstructure of spheroidite. The results were presented graphically, and the fatigue strength of steel with a varied share of non-metallic inclusions was determined during rotary bending. The results revealed that fatigue strength is determined by the relative volume of fine non-metallic inclusions and tempering temperature.

Providing an accurate count of total leukocytes and specific subsets (such as T-cells and B-cells) within small amounts of whole blood is a rather challenging ordeal due to the lack of techniques that enable the separation of leukocytes from a limited amount of whole blood. In a previous study we designed a microfluidic chip utilizing a micropillar array to isolate T-cells and B-cells from the sub-microliter of whole blood. Due to the variability of cells in size, morphology and color intensity, a Histogram of Oriented Gradients (HOG) based Support Vector Machine (SVM) classifier was proposed with an average accuracy of 94%, specificity of 99% and sensitivity of 90%. The HOG can separate the cells from the background with a high accuracy rate however, some noise is similar in shape and size to the actual cells and this results in misclassification. To alleviate this situation, in this study a convolutional neural network is trained and used to distinguish T-cells and B-cells with an accuracy rate of 98%, a specificity of 99% and a sensitivity of 97%. We also propose an HOG feature based SVM classifier to preselect the detection windows to accelerate the detection to process images in less than 10 min. The proposed on-chip cell detecting and counting method will be useful for numerous applications in diagnosis and for monitoring diseases.

We present a facial wearable robot to support eyelid movement for patients with hemifacial paralysis. People with facial paralysis are not able to blink, which leads to dry eyes and could cause permanent damage to the cornea. To address this issue, we developed a robotic system to support eyelid movement on the paralyzed side based on voluntary eyelid movement on the healthy side. The robot has a novel mechanism for supporting eyelid movement and is made from soft material, which we call the eyelid gating mechanism (ELGM). We defined the requirements for eyelid manipulation. Then, we introduced design rules for the ELGM based on this definition, and conducted a deformation analysis. As a result, we could control deformation so that it is tailored to eyelid movement with simple rotational input at two hinged ends. This system provides appropriate support for eyelid movement in a non-invasive and gentle manner, based on voluntary eyelid movement on the healthy side. In this paper, we present a performance evaluation of the developed ELGM and the wearable facial robot. We confirm that ELGM could aid eyelid closure in 8 out of 10 patients. Further, we find that the time lag between eyelid closure detection and completion was $$236.9 \pm 19.4$$ ms.

The study presents the results of analysis of the possibilities of measuring equipment supervision, taking into account the requirements of the ISO 9001: 2015 standard and risk management present there. As it has been shown, it is possible to use (mentioned in point 6.1 of indicated standard) a risk management method for skilfully managing a measuring equipment. Orientation of business to risk is one of the elements of the ISO 9001 standard, which does not specify exactly how the method of its implementation should looks like. Generally, it orders to manage risk wherever goals appear. The targets also appear in the field of supervision of measuring equipment. Therefore, in the elaboration, apart from the requirements analysis, the concept of a five-stage methodology for implementing a risk-based approach to management of measurement equipment was presented. The matrix method was used to assess the risk. Within this method two elements were assessed: probability and potential effects of the risk occurrence. Application of the proposed concept may contribute to a more efficient and effective management of measuring instruments.

Today’s market determinants and most importantly, very dynamically changing customer requirements significantly shortened the product life cycle. This situation reflects in companies by common extension of the assortment offered and personalised serial production. The result of a flexible approach to market changes is the implementation of LEAN concept, which, both in terms of management and production aims to develop efficiency within an organisation, which will then enable quick and dynamic response to changes in the environment. The popularity of LEAN concept (in management and production) among managers comes from its universality and a wide range of instruments used to maximise the use of existing potential. The main assumptions of LEAN concept are aimed at the maximum use of an organisation’s resources, defining the activities necessary to execute an order and identifying the areas generating losses and then minimising them and eventually eliminating. LEAN concept is based on flagship-main tools for identification and modernisation of processes, the difficulty in using them results from the need to recognise and select the most effective ones that meet the expectations of a given organisation. The article presents issues related to the first stage of implementing LEAN concept in a company’s structures, i.e. identification of opportunities and selection of appropriate tools.

This paper introduces a case study on the potential of new mechatronic chassis systems for battery electric vehicles, in this case a brake-by-wire (BBW) system and in-wheel propulsion on the rear axle combined with an integrated chassis control providing common safety features like anti-lock braking system (ABS), and enhanced functionalities, like torque blending. The presented controller was intended to also show the potential of continuous control strategies with regard to active safety, vehicle stability and driving comfort. Therefore, an integral sliding mode (ISM) and proportional integral (PI) control were used for wheel slip control (WSC) and benchmarked against each other and against classical used rule-based approach. The controller was realized in MatLab/Simulink and tested under real-time conditions in IPG CarMaker simulation environment for experimentally validated models of the target vehicle and its systems. The controller also contains robust observers for estimation of non-measurable vehicle states and parameters e.g., vehicle mass or road grade, which can have a significant influence on control performance and vehicle safety.

This paper presents a general methodology for the analysis and synthesis of a positive semi-definite system described by mass, damping and stiffness matrices that is often encountered in impedance control in robotics research. This general methodology utilizes the fundamental kinematic concept of rigid-body and non-rigid-body motions of which all motions consist. The rigid-body mode results in no net change in the potential energy from the stiffness matrix of the multiple degree-of-freedom (DoF) discrete mechanical system. Example of an unconstrained discrete mechanical system is presented to illustrate the theoretical principle as applied in obtaining the free and forced vibration responses, as well as the dynamic characteristics of the system in natural frequency, $$\omega_n$$ ω n and damping ratio, $$\zeta$$ ζ . In addition, the methodology is applied to the impedance control of redundant robots. The rigid-body mode is equivalent to the motions of a redundant robot which result in no net change in potential energy, also called the zero-potential or ZP mode, of impedance control. Example of a redundant robot is used to demonstrate the application of the methodology in robotics. The dynamic characteristics of $$\omega _n$$ ω n and $$\zeta$$ ζ in the modal space are analyzed, which can be synthesized to modulate the damping of the system analytically.

Tierwohl ist ein Qualitätsmerkmal moderner Schweinehaltung und zunehmend im Blickpunkt der Öffentlichkeit. Tierwohlrisiken sind multifaktoriell und müssen erkannt werden, bevor das Tierwohl gefährdet ist. Diese Arbeit nutzt Maschinelles Lernen (ML) zur frühzeitigen Prognose von Tierwohlrisiken. Der verwendete Datensatz umfasst Daten von über 57.000 Schweinen, gegliedert nach 10 Tierwohlrisiken und 14 Indikatoren für die Säugephase. Der zentrale Beitrag ist ein ML-Modell zur Prognose von Todesfällen in der Säugephase mit einer Accuracy von 80,4 %. Die Accuracy des Majority-Vote-Klassifikators für den Todesfall in der Säugephase beträgt hingegen nur 53,1 %. Somit könnte die Methode dazu beitragen, drohende Todesfälle in der Säugephase von Schweinen frühzeitig zu erkennen und Maßnahmen zu ergreifen., LANDTECHNIK, Bd. 76 Nr. 1 (2021)

Power soft robots—defined as novel robots driven by powerful soft actuators, achieving both powerfulness and softness—are potentially suitable for complex collaborative tasks, and an approach to actuating a power soft robot is the McKibben artificial muscle. This study aims to show the potential of hydraulic artificial muscles to be implemented in a power soft robot with high safety, including higher stability against sudden load separation or impact disturbance, and appropriate dynamic compliance. The stability of a manipulator arm driven by hydraulic muscle actuators is experimentally proven to be higher than that of pneumatic muscle actuators when the stored elastic energy is instantaneously released. Therefore, the hydraulic muscle actuator is a better candidate for actuating a power soft robot. By taking advantage of the incompressible liquid medium and the compliant structure of a hydraulic muscle, a second-order impedance control strategy with a braking method is proposed to improve dynamic compliance without sacrificing the safety features of hydraulic muscles. The results show that the manipulator can be easily shifted by a several-kilogram-level external force and react safely against sudden load change with low angular velocity by the proposed impedance control.

In the past few years, portable and smartphone-based diagnostic technologies have found their way into the agri-food industry. The aim of this research was to evaluate the performance of portable near-infrared (NIR) spectrometers, so called food-scanners, with regard to their predictive accuracy of important quality parameters of fruit and vegetables. Food-scanner measurements were performed in combination with destructive measurements of the corresponding quality trait (sugar content, dry matter, relative water content) on a wide range of produce from the fruit and vegetable assortment. This study evaluated dry matter content of apple, avocado, blueberry, table grape and tangerine, which yielded cross validation results (r²) of up to 0.95, 0.87, 0.94, 0.92 and 0.92 respectively. Furthermore, the evaluation of food-scanner spectra for the prediction of sugar content of blueberry, kiwi, mango, persimmon, table grape, tangerine and tomato yielded cross validations (r²) of up to 0.95, 0.84, 0.80, 0.75, 0.95, 0.93, and 0.87. Furthermore, relative water content of ginger obtained a cross validation correlation of r² = 0.91. The results show that these traits can be predicted with a high degree of accuracy using non-destructive measurements performed with three commercially available food-scanners SCiO™, F-750 Produce Quality Meter, and H-100F. Consequently, food-scanners can be used as objective measurement tools along the supply chain of fresh produce to quickly determine fruit quality. In addition, a practical example shows the potential of these instruments for non-destructive quality assessment in incoming goods control at fruit and vegetable wholesalers over a time period of several weeks. Furthermore, possible areas of application of food-scanners along the supply chain of fresh produce are discussed, possibilities for practical applications are presented and time-saving means are highlighted., Agricultural Engineering, Bd. 76 Nr. 1 (2021)

As a consequence of rapid ongoing technological developments and increasing integration into agricultural mechanization and agricultural intelligence, UAVs are gradually starting to play an increasingly important role in field crop management and monitoring. This review introduces and covers the development in four major applications of UAVs in maize production: (i) water stress detection, (ii) weed mapping, (iii) nutrient status monitoring and (iv) yield prediction. In addition, this review summarizes UAV data management methods, explains how expert systems work in UAV systems, and provides standardized workflow data for farmers in maize production. In addition, the strengths, weaknesses, opportunities, and threats of UAV use in maize production are analyzed. Based on more than eighty publications and our own research, the discussion and conclusions point out key issues in UAV usage in maize cropping and research gaps that need to be filled, along with a number of recommendations for the development of UAVs in maize production in the future., Agricultural Engineering, Bd. 76 Nr. 1 (2021)

This paper aims to find a mathematical justification for the non-linear steady state steering haptic response as a function of driver arm posture. Experiments show that different arm postures, that is, same hands location on the steering wheel but at different initial steering angles, result in a change in maximum driver arm stiffness. This implies the need for different steering torque response as a function of steering angle, which is under investigation. A quasi-static musculoskeletal driver model considering elbow and shoulder joints is developed for posture analysis. The torque acting in the shoulder joint is higher than in the elbow. The relationship between the joint torque and joint angle is linear in the shoulder, whereas the non-linearity occurs in the elbow joint. The simulation results qualitatively indicate a similar pattern as compared to the experimental muscle activity results. Due to increasing muscle non-linearity at high steering angles, the arm stiffness decreases and then the hypothesis suggests that the effective steering stiffness is intentionally reduced for a consistent on-center haptic response.