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With the advent of robotics and artificial intelligence, the potential for automating tasks within human-centric environments has increased significantly. This is particularly relevant in the retail sector where the demand for efficient operations and the shortage of labor drive the need for rapid advancements in robot-based technologies. Densely packed retail shelves pose unique challenges for robotic manipulation and detection due to limited space and diverse object shapes. Vacuum-based grasping technologies offer a promising solution but face challenges with object shape adaptability. The study proposes a framework for robotic grasping in retail environments, an adaptive vacuum-based grasping solution, and a new evaluation metric—termed grasp shear force resilience—for measuring the effectiveness and stability of the grasp during manipulation. The metric provides insights into how retail objects behave under different manipulation scenarios, allowing for better assessment and optimization of robotic grasping performance. The study's findings demonstrate the adaptive suction cups' ability to successfully handle a wide range of object shapes and sizes, which, in some cases, overcome commercially available solutions, particularly in adaptability. Additionally, the grasp shear force resilience metric highlights the effects of the manipulation process, such as in shear force and shake, on the manipulated object. This offers insights into its interaction with different vacuum cup grasping solutions in retail picking and restocking scenarios. [ABSTRACT FROM AUTHOR]

Asparagus harvesting presents unique challenges, due to the variability in spear growth, which makes large-scale automated harvesting difficult. This paper describes the development of an asparagus harvesting robot system. The system consists of a delta robot mounted on a mobile track-based platform. It employs a real-time asparagus detection algorithm and a sensory system to determine optimal harvesting points. Low-level control and high-level control are separated in the robot control. The performance of the system was evaluated in a laboratory field mock-up and in the open field, using asparagus spears of various shapes. The results demonstrate that the system detected and harvested 88% of the ready-to-harvest spears, with an average harvesting cycle cost of 3.44 s ± 0.14 s . In addition, outdoor testing in an open field demonstrated a 77% success rate in identifying and harvesting asparagus spears. [ABSTRACT FROM AUTHOR]

Patients after stroke need to re-learn functional movements required for independent living throughout the rehabilitation process. In the study, we used a wearable sensory system for monitoring the movement of the upper limbs while performing activities of daily living. We implemented time-based and path-based segmentation of movement trajectories and muscle activity to quantify the activities of the unaffected and the affected upper limbs. While time-based segmentation splits the trajectory in quants of equal duration, path-based segmentation isolates completed movements. We analyzed the hand movement path and forearm muscle activity and introduced a bimanual movement parameter, which enables differentiation between unimanual and bimanual activities. The approach was validated in a study that included a healthy subject and seven patients after stroke with different levels of disabilities. Path-based segmentation provides a more detailed and comprehensive evaluation of upper limb activities, while time-based segmentation is more suitable for real-time assessment and providing feedback to patients. Bimanual movement parameter effectively differentiates between different levels of upper limb involvement and is a clear indicator of the activity of the affected limb relative to the unaffected limb. [ABSTRACT FROM AUTHOR]

This paper investigates the feasibility of redirecting the field of view (FOV) of a light-based time-of-flight (ToF) ranging device, commonly known as a pulsed lidar, using fixed mirrors and prisms for possible future use in robotics. The emphasis is on configurations where the FOV redirection element is positioned beyond the ranging device's dead zone. A custom made direct ToF ranging device with time-over-threshold (TOT)-based walk error compensation was used to evaluate the effects of the FOV redirecting optics on range measurement accuracy and precision. The tests include redirecting the FOV with a clean prism with anti-reflective (AR) coating on its legs, as well as with a regular and a first surface mirror in both a clean and dusted state. The study finds the prism to be unsuitable due to parasitic reflections, which ruin the ranging data. The clean mirrors were found to have no noticeable effect on ranging accuracy. When they are dusty, mirrors introduce a negative measurement error. This effect is the most pronounced when a mirror is positioned toward the end of the partial dead zone of the ToF rangefinder, but loses influence as the mirror is moved farther away. The error is attributed to the parasitic reflection off dust on the mirror, which reduces the time of detection of the pulse reflected off the real target, and interferes with the walk error compensation by widening the detected pulse. [ABSTRACT FROM AUTHOR]

This study focuses on the feasibility of collaborative robot implementation in a medical microbiology laboratory by demonstrating fine tasks using kinesthetic teaching. Fine tasks require sub-millimetre positioning accuracy. Bacterial colony picking and identification was used as a case study. Colonies were picked from Petri dishes and identified using matrix-assisted laser desorption/ionization (MALDI) time-of-flight (TOF) mass spectrometry. We picked and identified 56 colonies (36 colonies of Gram-negative Acinetobacter baumannii and 20 colonies of Gram-positive Staphylococcus epidermidis). The overall identification error rate was around 11%, although it was significantly lower for Gram-positive bacteria (5%) than Gram-negative bacteria (13.9%). Based on the identification scores, it was concluded that the system works similarly well as a manual operator. It was determined that tasks were successfully demonstrated using kinesthetic teaching and generalized using dynamic movement primitives (DMP). Further improvement of the identification error rate is possible by choosing a different deposited sample treatment method (e.g., semi-extraction, wet deposition). [ABSTRACT FROM AUTHOR]

Due to the ageing population and an increasing number of stroke patients, we see the potential future of rehabilitation in telerehabilitation, which might alleviate the workload of physiotherapists and occupational therapists. In order to enable the use of telerehabilitation, devices aimed for home and independent use need to be developed. This paper describes the design of a robotic device for post-stroke wrist and finger rehabilitation and evaluates the movement it can perform. Six healthy subjects were tested in three experimental conditions: performing a coupled movement of wrist and fingers from flexion to extension without the device, with a passive device, and with an active device. The kinematics of the hand were captured using three Optotrak Certus motion capture systems and tracking 11 infrared active light-emitting diode (LED) markers. The results are presented in the form of base-line trajectories for all middle finger (MF) joints. In addition, the deviations of trajectories between conditions across all subjects were computed for the metacarpophalangeal (MCP) joint and fingertip of the MF and pinkie (PF) finger. Deviations from the base-line trajectory between measurement protocols and the root-mean-square deviation (RMSD) values indicate that the motion of the hand, imposed by the developed device, is comparable to the unconstrained motion of the healthy subjects, especially when moving into the extension, opening the hand. [ABSTRACT FROM AUTHOR]

We describe the Wearable Sensory Apparatus (WSA) System, which has been implemented and verified in accordance with the relevant standards. It comprises the Inertial Measurement Units (IMUs), real-time wireless data transmission over Ultrawideband (UWB), a Master Unit and several IMU dongles forming the Wireless Body Area Network (WBAN). The WSA is designed for, but is not restricted to, wearable robots. The paper focuses on the topology of the communication network, the WSA hardware, and the organization of the WSA firmware. The experimental evaluation of the WSA incorporates the confirmation of the timing using the supply current WSA profile, measurements related to determining the less error prone position of the master device on the backpack, measurements of the quality of the data transfer in a real environment scenario, measurements in the presence of other microwave signals, and an example of raw IMU signals during human walking. Placement of the master device on the top of the backpack was found to be less error prone, with less than 0.02% packet loss for all the IMU devices placed on different body segments. The packet loss did not change significantly in public buildings or on the street. There was no impact of Wi-Fi bands on the WSA data transfer. The WSA hardware and firmware passed conformance testing in a certified lab. Most importantly, the WSA performed reliably in the laboratory and in clinical tests with exoskeletons and prostheses. [ABSTRACT FROM AUTHOR]

In our study a robot was used to deliver objects for measurement into the Equator gauging system. To investigate the robot's manipulation influence on dimensional measurements, the robot's tasks were divided into basic functions. Based on these basic functions, nine different robot-manipulation scenarios were defined, i.e., from zero to full robot manipulation, for two measuring objects (named Magnet and PKR) and six measurement characteristics (rectangular and spherical). The robot's manipulation influence was determined on the basis of the statistical parameters C p , R, and the 6 σ obtained from a measurement system analysis (MSA) type-1 study. The results show that the degree of implemented manipulation of the robot affects the scattering of the measurement data. However, the effect is much more pronounced in the case of length measurements than with spherical geometries. Different measuring methods (touch-triggering or scanning measurement mode, number of sampling points) were used, which showed similar measurement data. This directly indicated the influence of the robot's manipulation on C p , R and 6 σ . Increasing the degree of the robot's manipulation decreases the C p value and increases the R and 6 σ values for the length measurements. There is no such pronounced course in the spherical geometries, where the values of C p , R and 6 σ remain approximately the same. The main influential factor for decreasing the C p value with increasing robot manipulation was the angular misalignment of the object's orientation in the fixture. [ABSTRACT FROM AUTHOR]

In patients after stroke, ability of the upper limb is commonly assessed with standardised clinical tests that provide a complete upper limb assessment. This paper presents quantification of upper limb movement during the execution of Action research arm test (ARAT) using a wearable system of inertial measurement units (IMU) for kinematic quantification and electromyography (EMG) sensors for muscle activity analysis. The test was executed with each arm by a group of healthy subjects and a group of patients after stroke allocated into subgroups based on their clinical scores. Tasks were segmented into movement and manipulation phases. Each movement phase was quantified with a set of five parameters: movement time, movement smoothness, hand trajectory similarity, trunk stability, and muscle activity for grasping. Parameters vary between subject groups, between tasks, and between task phases. Statistically significant differences were observed between patient groups that obtained different clinical scores, between healthy subjects and patients, and between the unaffected and the affected arm unless the affected arm shows normal performance. Movement quantification enables differentiation between different subject groups within movement phases as well as for the complete task. Spearman's rank correlation coefficient shows strong correlations between patient's ARAT scores and movement time as well as movement smoothness. Weak to moderate correlations were observed for parameters that describe hand trajectory similarity and trunk stability. Muscle activity correlates well with grasping activity and the level of grasping force in all groups. [ABSTRACT FROM AUTHOR]

This study uses inertial sensors to measure ski jumper kinematics and joint dynamics, which was until now only a part of simulation studies. For subsequent calculation of dynamics in the joints, a link-segment model was developed. The model relies on the recursive Newton-Euler inverse dynamics. This approach allowed the calculation of the ground reaction force at take-off. For the model validation, four ski jumpers from the National Nordic center performed a simulated jump in a laboratory environment on a force platform; in total, 20 jumps were recorded. The results fit well to the reference system, presenting small errors in the mean and standard deviation and small root-mean-square errors. The error is under 12% of the reference value. For field tests, six jumpers participated in the study; in total, 28 jumps were recorded. All of the measured forces and moments were within the range of prior simulated studies. The proposed system was able to indirectly provide the values of forces and moments in the joints of the ski-jumpers' body segments, as well as the ground reaction force during the in-run and take-off phases in comparison to the force platform installed on the table. Kinematics assessment and estimation of dynamics parameters can be applied to jumps from any ski jumping hill. [ABSTRACT FROM AUTHOR]

Previous studies have presented algorithms for detection of turns during gait using wearable sensors, but those algorithms were not built for real-time use. This paper therefore investigates the optimal approach for real-time detection of planned turns during gait using wearable inertial measurement units. Several different sensor positions (head, back and legs) and three different detection criteria (orientation, angular velocity and both) are compared with regard to their ability to correctly detect turn onset. Furthermore, the different sensor positions are compared with regard to their ability to predict the turn direction and amplitude. The evaluation was performed on ten healthy subjects who performed left/right turns at three amplitudes (22, 45 and 90 degrees). Results showed that turn onset can be most accurately detected with sensors on the back and using a combination of orientation and angular velocity. The same setup also gives the best prediction of turn direction and amplitude. Preliminary measurements with a single amputee were also performed and highlighted important differences such as slower turning that need to be taken into account. [ABSTRACT FROM AUTHOR]

This paper presents a gait phase detection algorithm for providing feedback in walking with a robotic prosthesis. The algorithm utilizes the output signals of a wearable wireless sensory system incorporating sensorized shoe insoles and inertial measurement units attached to body segments. The principle of detecting transitions between gait phases is based on heuristic threshold rules, dividing a steady-state walking stride into four phases. For the evaluation of the algorithm, experiments with three amputees, walking with the robotic prosthesis and wearable sensors, were performed. Results show a high rate of successful detection for all four phases (the average success rate across all subjects >90%). A comparison of the proposed method to an off-line trained algorithm using hidden Markov models reveals a similar performance achieved without the need for learning dataset acquisition and previous model training. [ABSTRACT FROM AUTHOR]

We present a sensor technology for the measure of the physical human-robot interaction pressure developed in the last years at Scuola Superiore Sant'Anna. The system is composed of flexible matrices of opto-electronic sensors covered by a soft silicone cover. This sensory system is completely modular and scalable, allowing one to cover areas of any sizes and shapes, and to measure different pressure ranges. In this work we present the main application areas for this technology. A first generation of the system was used to monitor human-robot interaction in upper- (NEUROExos; Scuola Superiore Sant'Anna) and lower-limb (LOPES; University of Twente) exoskeletons for rehabilitation. A second generation, with increased resolution and wireless connection, was used to develop a pressure-sensitive foot insole and an improved human-robot interaction measurement systems. The experimental characterization of the latter system along with its validation on three healthy subjects is presented here for the first time. A perspective on future uses and development of the technology is finally drafted. [ABSTRACT FROM AUTHOR]

An ultra-wideband (UWB) localization system is an alternative in a GPS-denied environment. However, a distance measurement with UWB modules using a two-way communication protocol induces an orientation-dependent error. Previous research studied this error by looking at parameters such as the received power and the channel response signal. In this paper, the neural network (NN) method for correcting the orientation-induced distance error without the need to calculate the signal strength, obtain the channel response or know any parameters of the antenna and the UWB modules is presented. The NN method utilizes only the measured distance and the tag orientation, and implements an NN model obtained by machine learning, using measurements at different distances and orientations of the two UWB modules. The verification of the experimental setup with 12 anchors and a tag shows that with the proposed NN method, 5 cm better root mean square error values (RMSEs) are obtained for the measured distance between the anchors and the tag compared to the calibration method that did not include orientation information. With the least-square estimator, 14 cm RMSE in 3D is obtained with the NN model corrected distances, with a 9 cm improvement compared to when raw distances are used. The method produces better results without the need to obtain the UWB module's diagnostics parameters that are required to calculate the received signal strength or channel response, and in this way maintain the minimum packet size for the ranging protocol. [ABSTRACT FROM AUTHOR]

Estimation of the centre of pressure (COP) is an important part of the gait analysis, for example, when evaluating the functional capacity of individuals affected by motor impairment. Inertial measurement units (IMUs) and force sensors are commonly used to measure gait characteristic of healthy and impaired subjects. We present a methodology for estimating the COP solely from raw gyroscope, accelerometer, and magnetometer data from IMUs using statistical modelling. We demonstrate the viability of the method using an example of two models: a linear model and a non-linear Long-Short-Term Memory (LSTM) neural network model. Models were trained on the COP ground truth data measured using an instrumented treadmill and achieved the average intra-subject root mean square (RMS) error between estimated and ground truth COP of 12.3 mm and the average inter-subject RMS error of 23.7 mm which is comparable or better than similar studies so far. We show that the calibration procedure in the instrumented treadmill can be as short as a couple of minutes without the decrease in our model performance. We also show that the magnetic component of the recorded IMU signal, which is most sensitive to environmental changes, can be safely dropped without a significant decrease in model performance. Finally, we show that the number of IMUs can be reduced to five without deterioration in the model performance. [ABSTRACT FROM AUTHOR]

Wearable robotic devices require sensors and algorithms that can recognize the user state in real-time, in order to provide synergistic action with the body. For devices intended for locomotion-related applications, shoe-embedded sensors are a common and convenient choice, potentially advantageous for performing gait assessment in real-world environments. In this work, we present the development of a pair of pressure-sensitive insoles based on optoelectronic sensors for the real-time estimation of temporal gait parameters. The new design makes use of a simplified sensor configuration that preserves the time accuracy of gait event detection relative to previous prototypes. The system has been assessed relatively to a commercial force plate recording the vertical component of the ground reaction force (vGRF) and the coordinate of the center of pressure along the so-called progression or antero-posterior plane (CoPAP) in ten healthy participants during ground-level walking at two speeds. The insoles showed overall median absolute errors (MAE) of 0.06 (0.02) s and 0.04 (0.02) s for heel-strike and toe-off recognition, respectively. Moreover, they enabled reasonably accurate estimations of the stance phase duration (2.02 (2.03) % error) and CoPAP profiles (Pearson correlation coefficient with force platform ρCoP = 0.96 (0.02)), whereas the correlation with vGRF measured by the force plate was lower than that obtained with the previous prototype (ρvGRF = 0.47 (0.20)). These results confirm the suitability of the insoles for online sensing purposes such as timely gait phase estimation and discrete event recognition. [ABSTRACT FROM AUTHOR]

This paper explores the possibility of distributing the fields of view (FOVs) of a centralized lidar cluster using fixed mirrors for future use in safety applications in robotics and elsewhere. A custom modular lidar system with time-over-threshold (TOT) walk error compensation was developed for the experiments. It comprises a control board that provides the processing power and adjustable voltage regulation, and multiple individually addressable analogue front end (AFE) boards that each contain a transmitter, a receiver, time-to-digital (TDC) converters for pulse width measurements on the bot Tx and Rx side, and adjustable reference voltage generators for both the Tx and Rx pulse detection threshold. The lidar system's performance with a target in the direct line of sight is compared to the configurations where the FOV is redirected with up to three mirrors in different configurations. The results show that the light path through the neighboring mirrors introduces a minor but noticeable measurement error on a portion of the measurement range.