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For high-precision contouring tasks in a typical Cartesian motion system, multiaxis cooperation is a long-standing challenging issue. Inevitably, various factors pose substantial difficulty in the multiaxis cooperation leading to degraded contouring performance, such as the strong coupling effect between different axes, nonlinearity, the unknown dynamics due to the friction, and the difficulties in accurate system identification. To enhance the contouring performance of a flexure-joint dual-drive gantry system against the aforementioned issues, this article presents a hybrid active–passive robust control framework leveraging a model-free architecture. In this control scheme, all the coupling effects, nonlinearity, disturbance, and unknown dynamics are considered as “lumped uncertainty”. Then, a super-twisting sliding mode control method with a signum-type iterative learning law is proposed to passively suppress the lumped uncertainty during iterations; and an extended state observer is deployed to actively compensate the lumped uncertainty and ensure the establishment of sliding motion in the time domain. As supported by theoretical analysis, the proposed controller is shown to exhibit several important properties. First, the establishment of the sliding motion is guaranteed globally, in both the time domain and the iteration domain. Second, the properties of short establishment time of the sliding motion, fast convergence during the iterations, and low chattering are achieved. Moreover, a series of comparative experiments are conducted, and the proposed method is shown to be rather effective in achieving excellent contouring performance in the high-speed and complex-curvature contouring tasks, without relying on the system model. [ABSTRACT FROM AUTHOR]

This article introduces a method for efficient and robust free-positioning wireless power transfer (WPT) in a large area, which can be applied to many use cases, including wireless charging of industrial robots, drones, and electric scooters. In these large areas of WPT applications, multiple transmitters (Txs) are placed in a pad-like area, and the Tx coils are optimally excited to enable robust and efficient power transfer to movable receivers within the charging area. The proposed configuration enables almost continuous magnetic flux path from a set of Tx coil(s) to another set of Tx coil(s) through the receiver coil ferrite core. Therefore, efficient power transfer is ensured throughout the whole Tx coverage area. The article introduces a novel method to detect the position and orientation of the receiver only from the Tx-side measurements. The proposed solution is experimentally verified in a laboratory prototype, and the experimental results show dc-to-dc efficiency of 91% with only 1% variation in most of the Rx positions. [ABSTRACT FROM AUTHOR]

Due to the wide distribution and high energy-saving potential of industrial robots, energy optimization techniques of industrial robots attract increasing attention. Dynamic time-scaling methods can optimize the energy consumption of robots only by stretching or shrinking reference trajectories in the time dimension. Dynamic time-scaling methods show advantages over other energy-saving techniques because time-scaling methods can achieve energy savings without hardware investment. Traditional dynamic time-scaling methods need to search the possible state transitions from the initial configuration to the final configuration to obtain the optimal solution. The integration of robot transient power has to be carried out for each possible state transition, which directly leads to intensive computation. Therefore, in this article, an efficient computation method for robot trajectory optimization is proposed. Based on parameter separation, an energy characteristic parameter model based on the dynamic time-scaling is developed, which describes the energy consumption during the state transition as a function of the scaling parameters. Based on the energy characteristic parameter model, the dynamic programming algorithm can replace the integral operation of transient power with the substitution calculations, which avoids intensive computation. Experimental results show that the proposed method can achieve 33.7% less energy consumption, and the computation time can be reduced by nearly 99%. [ABSTRACT FROM AUTHOR]

This article presents the integrated design of a robot-based inline measurement system for precise 3-D surface inspection on free-formed objects. The measurement system comprises a MAGLEV measurement platform that is mounted to an industrial robot and enables the out-of-plane tracking of an arbitrarily oriented sample surface. This establishes lab-like conditions for the integrated optical 3-D measurement tool directly in a vibrational environment. Using a proportional-integral-derivative control architecture with a tracking control bandwidth of 600 Hz, the effects of a vibration signal with 15.5 $\mu$ m rms can be reduced to disturbances with 236 nm rms. The orientation-independent measurement performance is demonstrated by imaging a calibration standard with 20 $\mu$ m pitch in various robot poses. Experiments show that the system is capable of reducing the axial measurement uncertainty by a factor of 12, enabling robot-based 3-D measurements with submicrometer resolution on freeform surfaces in a vibrational environment. [ABSTRACT FROM AUTHOR]

This article proposes a novel interaction force estimation scheme capable of estimating the interaction forces for industrial robots with high precision in the absence of force sensors. Specifically, we first establish the dynamic model of a class of industrial robots via model identification methods. Furthermore, a high-order finite-time observer (HOFTO) is established to estimate the interaction forces, where HOFTO serves as an interaction force observer and is designed to accurately estimate external time-varying interaction forces. In addition, we strictly analyze the stability of our approach in two different cases, endowing HOFTO with reliable estimation abilities in broader applications. Subsequently, we integrate the estimated force information into the applications of force control frameworks (e.g., collision detection and impedance control). Several evaluations on a real 6-axes robot demonstrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

The pose estimation is the critical technology in industrial robot. Nowadays, many machine vision-based approaches have applied the technology and achieved excellent results. However, the rapid detection of the pose estimation in complex multiscene environments is still a challenge, due to the interference of multiangle light and multibackground. To address these issues, this article proposes a practical robotic grasping method by using the 6-D pose estimation with protective correction. In this method, the synthetic dataset by self-production is used to train the improved deep object pose estimation network and then use the standard perspective-n-point algorithm to estimate the 6-DoF pose for each object instance. Meanwhile, in order to prevent grasp collisions cause by misrecognition, we propose the corrected grasping pose algorithm for protective correction by measured translation and predicted translation. Finally, the proposed grasping method has an average grasping success rate of 83.3% for the three objects under normal light, and the network for single-image detection speed has been to 1.490 frames/s. The code is available at https://github.com/aimiplus/Practical_Robotic_Grasping_Method. [ABSTRACT FROM AUTHOR]

Iterative learning control (ILC) has been well recognized for its output tracking ability in systems that perform repetitive tasks, such as robot manipulators. In practice, however, the application of ILC remains challenging as it generally requires the repetition of the initial settings and such industrial manipulators do not provide measurements of actual joint positions. This article presents a practical and fully automated implementation of ILC for industrial robot manipulators while assuming complete model uncertainty and the unavailability of joint velocity measurements. We propose the employment of a dedicated controller tasked only with bringing the arm back to its initial position while reducing the joint position reinitialization error after every iteration. We show that the convergence of the position tracking error is bounded by the initial mismatch. Finally, we provide experimental justification of the proposed approach on a 4-DOF commercial robot manipulator while only using the measurements of relative joint positions and show that our fully automated process outperforms two ILC algorithms with thorough manual homing. [ABSTRACT FROM AUTHOR]

This article presents a three-degree-of-freedom (DoF) magnetically levitated vibration compensating measurement platform (MP) with arbitrary operation orientation for robot-based surface inspection of free-forms. The MP design comprises an internal position sensor system, which is used in feedback control to maintain a free-floating position in six DoFs with respect to its supporting frame when approaching a sample (stabilization mode). In addition, the integrated design includes three tracking sensors measuring the out-of-plane position of the MP to a sample surface. The entire system can be mounted as an end-effector of an industrial robot with the MP carrying a desired measurement tool. Disturbing environmental vibrations are actively compensated by maintaining a constant position of the MP with respect to a sample surface (tracking mode). The control design includes single-input single-output position controllers for all DoFs, achieving a bandwidth of about 130 Hz. By means of a cross-fading error gain, an efficient control transition between stabilization and tracking mode is enabled. A vibrating target is used to evaluate the vibration compensation performance of the tracking module for standardized floor vibration profiles. Attenuation between 35 and 20 dB for out-of-plane vibrations below 40 Hz is achieved. In the time domain, vibration profiles with 15.7  $\mu$ m rms and 95  $\mu$ rad rms are reduced to 1.6  $\mu$ m rms and 21  $\mu$ rad rms, respectively. [ABSTRACT FROM AUTHOR]

Traditional surface permanent magnet synchronous motor (SPMSM) used as a servo motor limits the miniaturization and performance improvement of industrial robot, due to its large overall volume and heavy weight of the rotor. In this article, a novel transverse flux permanent magnet motor with a hybrid stator core and disk-type rotor (HSDR-TFPM) is proposed to adapt to the industrial robot well. Moreover, a better space design by which the usual components used in industrial robot is considered. Considering the computing time and accuracy, an analysis method based on Schwarz–Christoffel mapping is employed to analyze the magnetic field of HSDR-TFPM and conduct research on motor parameters. In order to prevent the axial movement of rotor, the detailed mechanical design is introduced and the strength of motor is analyzed further. In the end, the analysis results and performance of the proposed HSDR-TFPM are validated and compared with a conventional servo SPMSM. [ABSTRACT FROM AUTHOR]

Fault detection via power consumption monitoring of industrial robots is a substantial problem considered in this article, in which the healthy measurements of power consumption and encoders data for a prespecified task are employed as a reference for comparison to diagnose the potential failures or excessive degradation in the robot joints. Since most electrical and mechanical faults directly affect the consumed energy, the proposed solution analyzes the comparison outcomes between the healthy reference data with that monitored in a real time for each individual task. To integrate the power measurements with a base station, a ZigBee-based wireless data acquisition circuit has been developed to process the joints data. This article suggests a measurement-based mathematical model called Bode equations vector fitting as a robust fitting method to estimate such power consumption patterns. The achieved estimates allow a clear distinction for the potential failures in the robot joints that affect the power rate patterns even when involving sharp fluctuations. A table-based neural network classifier is presented to indicate the faulty joint or encoder according to the time intervals that divided for the executed task. The experimental results demonstrate the performance verification and feasibility of the proposed approach in ABB-IRB-1200 robot manipulator. [ABSTRACT FROM AUTHOR]

Multiple mobile robots have gradually played a key role in many industrial systems, such as factory freight logistics system, patrol security in the factory environment, and multirobot collaborative service and work. As a key issue in industrial environment perception, the accurate robot localization can enhance their autonomous ability and is an important branch of robotic studies in artificial intelligence. In this paper, we propose a new method for cooperative autonomous localization among air-ground robots in a wide-ranging outdoor industrial environment. The aerial robot first maps an area of interest and achieves self-localization. Then the aerial robot transfers a simplified orthogonal perspective 2.5-D map to the ground robots for collaboration. Within the collaboration, the ground robot achieves pose estimation with respect to the unmanned aerial vehicle pose by instantaneously registering a single panorama with respect to the 2.5-D map. The 2.5-D map is used as the spatial association among air-ground robots. The ground robots estimate the orientation using automatically detected geometric information and generates the translation by aligning the 2.5-D map with a semantic segmentation of the panorama. Our method effectively overcomes the dramatic differences between the air-level view and the ground-level view. A set of experiments is performed in the outdoor industrial environment to demonstrate the applicability of our localization method. The proposed robotic collaborative localization outperforms most consumer sensor in accuracy and also has an outstanding running time. [ABSTRACT FROM AUTHOR]

With the development of Industry 4.0, robots tend to be intelligent and collaborative. For one, robots can interact naturally with humans. For another, robots can work collaboratively with humans in a common area. The traditional teaching method is no longer suitable for the production mode with human–robot collaboration. Since the traditional teaching processes are complicated, they need highly skilled staffs. This paper focuses on the natural way of online teaching, which can be applied to the tasks such as welding, painting, and stamping. This paper presents an online teaching method with the fusion of speech and gesture. A depth camera (Kinect) and an inertial measurement unit are used to capture the speech and gesture of the human. Interval Kalman filter and improved particle filter are employed to estimate the gesture. To integrate speech and gesture information more deeply, a novel method of audio-visual fusion based on text is proposed, which can extract the most useful information from the speech and gestures by transforming them into text. Finally, a maximum entropy algorithm is employed to deal with the fusion text into the corresponding robot instructions. The practicality and effectiveness of the proposed approach were validated by five subjects without robot teaching skills. The results indicate that the online robot teaching system can successfully teach robot manipulators. [ABSTRACT FROM AUTHOR]

This paper presents a novel multivariable two-time scale control method for flexible joint robots. The fundamental limitations of the conventional two-time scale control are clearly explained based on a singular perturbation analysis with a linearized dynamic model. Unlike the conventional methods, the bandwidth of the slow control can be made high and the derivatives of the rigid control are not required. The closed-form solution of a slow model that is more accurate than the rigid model is presented. It is shown that the modeling error of the proposed two-time scale control can be made arbitrarily small by the control gain only. A real-world experiment with a six degrees-of-freedom commercial industrial robot was performed to validate the presented approach. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of path tracking of industrial robots. The main idea is to correct a preplanned path through an iterative learning control (ILC) method. Instead of seeking the conventional ILC strategy, an iterative learning identification method, which is called calibration-based ILC, is developed to identify the robot kinematic parameters along the path in a local working zone. To facilitate calibration-based ILC, we propose two objectives. The first objective is to find the exact values of robot kinematic parameters based on the ILC scheme. The second objective is to search the fastest learning convergence speed and robustness in the iterative domain. Based on the identification of robot kinematic parameters, we then propose an algorithm for the accurate path tracking of industrial robots. The simulation and experimental results demonstrate that the performance of path tracking can be improved significantly via the proposed method. [ABSTRACT FROM PUBLISHER]

A serial–parallel hybrid machine tool is expected to integrate the respective features of pure serial/parallel mechanism. The traditional method of hybridization is to connect $n$ $(n\geq 2)$ mechanisms bottom to head, in which at least one should be a parallel mechanism. One unique approach called Mechanism Hybridization is to embed one serial mechanism inside of a pure parallel mechanism, which greatly changes its overall performance. Based on this idea, an X–Y gantry system including a five-axis hybrid manipulator is developed, which is expected to be applied as the next generation of computer numerical control machine. The inverse kinematics and Jacobian matrix are derived. Since performance improvement is one of the most important factors that greatly affect the application potential of hybrid manipulators in different industry fields, to deeply investigate the comprehensive features, the local/global performance indexes of stiffness, dexterity, and manipulability are mathematically modeled and mapped. A discrete-boundary-searching method is developed to calculate and visualize the workspace. Pareto-based evolutionary multiobjective performance optimization is implemented to simultaneously improve the four indexes, and the representative nondominated solutions are listed. The proposed methodologies are generic and applicable for the design, modeling, and improvement of other parallel/hybrid robotic machine tools. [ABSTRACT FROM PUBLISHER]

This paper proposes a decoupled-space control (DSC) framework for spatial multi-degrees-of-freedom (DOF) parallel robots, to further improve the control performances of the currently studied control algorithms, via realizing the decoupling of the control space, using singular value decomposition (SVD) algorithms. Making use of the positive definite property of the mass/inertia matrix of spatial multi-DOF parallel robots, the decoupled matrix, an orthogonal matrix, can be derived by applying SVD algorithms. Through space transformation with the decoupled matrix, a spatial multi-DOF parallel robot model can be expressed in an uncoupled space. The independent control design can be implemented for each control channel in the uncoupled space, and the strongly dynamic coupling effects in the current control strategies can be removed. To confirm the proposed DSC framework, a simple controller, as an example, is developed in the decoupled space with the desired and real actuator position as its input and the valve command as its output. Under the proposed DSC strategy, the control performances of spatial multi-DOF parallel robots are evaluated in simulation and experiment. Results show that the DSC framework can further improve the control performances of the current control algorithms designed in the physical space of spatial multi-DOF parallel robots, by solving the problem of dynamic coupling effects. [ABSTRACT FROM PUBLISHER]

Wafer-handling robots are widely used to transfer wafers in semiconductor manufacturing. To improve the wafer transfer efficiency, optic sensors are installed at each station to estimate the wafer eccentricity on the fly. However, due to nonideal factors such as light beam radius, robot motion error, and system nonlinearity and uncertainties, it is difficult to achieve high-accuracy eccentricity estimation to satisfy the demanding requirements in semiconductor manufacturing. To further improve the eccentricity estimation accuracy, the relationship among the robot kinematic error, sensor calibration error, and eccentricity identification error is analyzed. The analytic results show that both the error modeling method and the global data sampling method can greatly improve the wafer eccentricity estimation accuracy. The proposed eccentricity estimation techniques are verified by experiments performed on a wafer-handling robotic system. The results demonstrate that the developed methods can be used to improve the wafer-handling accuracy and reduce the wafer-handling cycle time in semiconductor manufacturing. [ABSTRACT FROM PUBLISHER]

The performance of vision-based control systems, in particular, of highly dynamic vision-based motion control systems, is often limited by the low sampling rate of the visual feedback caused by the long image processing time. In order to overcome this problem, the networked visual servo control (NVSC), which integrates networked computational resources for cloud image processing, is considered in this paper. The main contributions of this paper are the following: 1) a real-time transport protocol for transmitting large-volume image data on a cloud-computing platform, which enables high-sampling-rate visual feedback; 2) a stabilizing control law for the NVSC system with time-varying feedback time delay; and 3) a sending rate scheduling strategy aiming at reducing the communication network load. The performance of the NVSC system with sending rate scheduling is validated in an object-tracking scenario on a 14-DOF dual-arm robot. Experimental results show the superior performance of our approach. In particular, the communication network load is substantially reduced by means of the scheduling strategy without performance degradation. [ABSTRACT FROM PUBLISHER]

This paper deals with vision-based elevator button recognition for a robot arm manipulating elevator buttons. The major difficulties in elevator button recognition are the presence of partial occlusion of the target objects and image clutter caused by specular reflection from mirrorlike walls inside the elevator. As a remedy for the elevator button recognition problem in highly complicated settings, we propose a robust button recognition algorithm, which is modularized into feature extraction, initial recognition, and postrefinement modules. In consideration of the diverse button shapes in the form of convex quadrilaterals with rounded button corners, a set of features is specially designed to describe each button contour subject to perspective distortion. A homography-based image transform is also employed for the template matching to achieve a more reliable matching performance. Like a grammar in linguistics, geometric button alignment, plays a key role in the elimination of false positives and the estimation of the missing buttons. The proposed algorithm is extensively tested in a robotic platform to verify effectiveness, robustness, and real-time performance. [ABSTRACT FROM PUBLISHER]

Battery state-of-charge (SOC) estimation is essential for a mobile robot, such as inspection of power transmission lines. It is often estimated using a Kalman filter (KF) under the assumption that the statistical properties of the system and measurement errors are known. Otherwise, the SOC estimation error may be large or even divergent. In this paper, without the requirement of the known statistical properties, a SOC estimation method is proposed using an H\infty observer, which can still guarantee the SOC estimation accuracy in the worst statistical error case. Under the conditions of different currents and temperatures, the effectiveness of the proposed method is verified in the laboratory and field environments. With the comparison of the proposed method and the KF-based one, the experimental results show that the proposed method can still provide accurate SOC estimation when there exist inexact or unknown statistical properties of the errors. The proposed method has been applied successfully to the robot for inspecting the running 500-kV extra high voltage power transmission lines. [ABSTRACT FROM PUBLISHER]

In this paper, a novel wire-based robot system with consideration of the different levels of wire rope tension is introduced, and its performance while executing a task in an unknown environment is analyzed. An adaptable wire rope tension control, called a twin direct-drive motor system, provides a unique structure for a robot interaction system. Compared with conventional industrial robots, it significantly becomes the preferred approach for improving the level of reliability and providing safe user interaction because the wire rope mechanism is a low friction and lightweight device. In addition, from the identification results, the bandwidth of the robot system can be regulated by changing the wire rope tension. In the controller design, dual disturbance observers with respect to two operation modes, namely, the common mode and the differential mode, are designed and applied for controlling the wire rope tension and interaction force. A variable wire rope tension algorithm is proposed to change the mechanical bandwidth based on the movements of a human. The advantages of a high mechanical bandwidth and low stiffness transmission are combined. With regard to the rejection of the vibration effects and the generation of a smooth interaction force, the variable wire rope tension control is found to give the best results in an experimental setup. [ABSTRACT FROM AUTHOR]

A robotic hardware-in-the-loop simulation platform was designed to aid in the synthesis and analysis of robot manipulators and their controllers. The platform uses a load emulation mechanism to apply nonlinear and coupled dynamic loads to the joint hardware. Some experimental results from a 5-DOF industrial manipulator are provided, demonstrating how the platform can simulate the performance of a manipulator under normal and aggressive operating conditions. [ABSTRACT FROM AUTHOR]

This paper aims to present a framework for the design and performance analysis of iterative learning control (ILC) for sampled-data systems. The analysis is presented in both time and frequency domains. Monotonic convergence criteria are derived in both time and frequency domains and coined in ILC designs. In particular, the causes or conditions that lead to the poor transient responses in the time domain are explored and disclosed. Four ILC designs associated with different learning functions and filters are considered, namely, the P-type, D-type, D^2-type, and general filters. The criteria for the selection of each type are presented. In addition, a relationship is shown between sampling-time selection and ILC convergence. Theoretical work concludes with a guideline for the ILC designs. Simulation results are shown to support the theoretical analysis in the time and frequency domains. Furthermore, based on the frequency-domain design tools, a successful experimental implementation on an electric piezomotor is demonstrated. [ABSTRACT FROM AUTHOR]

In the face of large-scale parametric uncertainties, the single-model (SM)-based sliding mode control (SMC) approach demands high gains for the observer, controller, and adaptation to achieve satisfactory tracking performance. The main practical problem of having high-gain-based design is that it amplifies the input and output disturbance as well as excites hidden unmodeled dynamics, causing poor tracking performance. In this paper, a multiple model/control-based SMC technique is proposed to reduce the level of parametric uncertainty to reduce observer-controller gains. To this end, we split uniformly the compact set of unknown parameters into a finite number of smaller compact subsets. Then, we design a candidate SMC corresponding to each of these smaller subsets. The derivative of the Lyapunov function candidate is used as a resetting criterion to identify a candidate model that approximates closely the plant at each instant of time. The key idea is to allow the parameter estimate of conventional adaptive sliding mode control design to be reset into a model that best estimates the plant among a finite set of candidate models. The proposed method is evaluated on a 2-DOF robot manipulator to demonstrate the effectiveness of the theoretical development. [ABSTRACT FROM AUTHOR]

Model-driven engineering (MDE) is proposed as the next revolution in embedded-system development. It is a promising paradigm that provides the developer the abstraction level required to focus on the specific application and not on the underlying computing environments. Real-time (RT) Linux variants constitute a mature and stable platform that can be considered a strong candidate for RT applications in the control and automation domain. In this paper, a framework for the MDE of industrial automation systems is presented. This framework exploits the following: 1) the function block, a well-known paradigm in the industrial automation domain, to provide the control engineer with the ability to construct its systems as aggregations of existing components and 2) the real-time Linux to execute the automatically synthesized executable. A prototype runtime environment is described, and a laboratory example application using a robotic arm is used to demonstrate the applicability of the proposed framework. Performance measurements are very promising, even for hard RT control applications. [ABSTRACT FROM AUTHOR]

A novel five-axes robot for industrial large printing applications is presented in this paper. The robot was developed in the robotics team from PRIME instituteref refid="fnote1"/ id="fnote1" asterisk="no"para Laboratoire de Mécanique des Solides.para and an international patent was deposited for this invention in 2006. It concerns large-format 3-D printing on a fixed surface, like trailer tarpaulin for example. The robot is composed of an inkjet printing block and a device to dry the ink sprayed onto the surface. Kinematics of the mechanical device with 5 DOF was studied to position and orientate the printheads onto the surface to be printed. The structure of the robot is simple with high-speed capability and printing resolution. The working principle and mechanical structure are described, and the geometrical model and surface following control of the robot are also discussed. Finally, printing results in a practical situation illustrate the efficiency of the proposed 3-D printing robot, and an analysis of how the task is carried out is provided. [ABSTRACT FROM AUTHOR]

In this paper, we consider the problem of designing a robust controller for a two-inertia system which contains arbitrarily large (but bounded) model uncertainties and disturbances. The research is motivated by the fact that a two-inertia system represents most of an industrial robot arm system that has a flexible joint, for which vibration suppression and robust control against model uncertainties and external disturbances are very important. The proposed controller consists of two parts: the outer-loop controller designed by the backstepping approach and the inner-loop controller by the new partial disturbance observer (DOB). The DOB is responsible for compensating the input-matched uncertainties and disturbances, while the backstepping controller is designed for dealing with the rest. The proposed controller makes tracking error and vibration of the system suppressed within an arbitrarily small bound during operation time when full states are measured. The results are verified by simulations and experiments with a Luenberger observer. [ABSTRACT FROM AUTHOR]

For time-delayed bilateral teleoperation systems, this paper presents a novel structure to considerably improve performance in terms of transparency and perception bandwidth, which are extremely low for passive systems, as well as force–position and velocity tracking on which delay control systems suffer both necessity for provision of identical initial conditions and drift problem. Performance improvement is carried out in three steps. The first step is the utilization of a four-channel wave-transmission structure that provides direct force and velocity feedbacks to each robot by asymmetric damping. Since the common dimension of wave variables is acceleration, the second step is the conversion of wave data into acceleration terms and the employment of acceleration control. The third step is the scaling of both the force- and position-based acceleration dimensions. Perception-bandwidth-limiting filters are used neither in wave space nor in control space. We showed the validity by experiments and superiority to previous systems by various comparative analyses. [ABSTRACT FROM PUBLISHER]

Safety of humans who work with robots is an important issue. Many studies have addressed related methods, but fundamental limits to meet safety requirements have been encountered owing to the absence of compliance in robot actuators. Pneumatic muscle (PM) is considered to be a basic actuator and offers the advantage of intrinsic elasticity to achieve joint compliance. In this paper, joint compliance actuated by PM is actively utilized to enhance human safety during collisions. To this end, the authors present a novel approach to control compliance and associated positions independently with no cross-performance effects using PMs. The proposed method is verified by experiments using a physical robot. In addition, methods to decrease damage from collisions between robots and humans due to operational faults are evaluated through experiments. The effectiveness of the proposed method is verified by measuring the impact impulse in collisions. [ABSTRACT FROM AUTHOR]

A new pipe inspection robot, called the National Taiwan University (NTU) Navigator, is described in this paper. The NTU Navigator is lightweight, modularly designed, and easily manipulated and repaired. The robot consists of camera, steering, driving, and functional mechanism modules. Each module has its own control circuit and functions. In addition, a new stretch mechanism is designed and optimized in order to adapt the robot to pipes of various radii. The robot can be easily controlled using GUI on a PC. A stable and smooth fuzzy steering controller for operating inside the pipes is constructed. The stability and performance of the fuzzy controller are shown and compared with both the conventional proportional-integral-derivative controller and the flatness-based controller. Simulations and experiments further justify the performance of the NTU Navigator. [ABSTRACT FROM AUTHOR]

This paper presents the UJI Industrial Robotics Telelaboratory, which lets Ph.D. and Master's degree students perform robotics and computer vision tele-experiments. By using this system, students are able to program experiments remotely via the Web, in order to combine the use of a field-programmable gate array (FPGA) to provide real-time vision processing, a conveyor belt, and a Motoman industrial manipulator. This paper introduces the novel SNRP protocol (i.e., Simple Network Robot Protocol), which permits the integration of network robots and sensors within an e-learning platform in a simple and reliable manner. As long as the students are able to interact remotely with a real robotic scenario, this system helps students very much to learn robotics control techniques like visual servoing control, vision for industrial applications, and robotics manipulation. The various components of the system are connected via a 100BaseT Ethernet network and follow the SNRP protocol, which grants simple access to generic networked devices using enhanced HTTP-based connections. Moreover, the whole telelaboratory is connected to the Internet through a router that permits the user to control the networked devices according to security constraints. The SNRP architecture is compared with a Common Object Request Broker Architecture-based approach, which was used in a previous telelaboratory. This paper describes two principle contributions: the design of a novel SNRP network architecture for the intercommunication of robots and sensors within an e-learning telelaboratory and the integration of a programmable FPGA vision system, which allows students to learn not only robotic techniques but also the design of high-performance circuits for industrial vision applications. [ABSTRACT FROM AUTHOR]

This paper presents a particular case of a pedagogically successful, dynamic, and efficient remote laboratory. The aim of the remote laboratory is to learn how to program embedded real-time systems in a real machine such as a robot. The system supplies feedback information to the user through a web browser and an ssh terminal. Likewise, the remote laboratory allows a high degree of interaction owing to a clear and simple interface. This type of telecontrol web-based system generates strong interest among students. The following are the two main contributions of this system: The remote laboratory allows collaboration among students in order to solve the problem, and the usage of a free software architecture allows anyone to replicate and improve the laboratory. [ABSTRACT FROM AUTHOR]

Service robots are spreading their application areas to human coexisting real environments. However, it is still difficult to find an autonomous robot that is capable of manipulation services in a real environment. The three major difficulties of manipulation service can be summarized as follows: 1) unstructured human-centered environment; 2) limited resources in a robot; and 3) uncertainties in real environments. This paper deals with the autonomous manipulation task by a service robot in human coexisting environment. We focus on a door-opening problem. In this paper, we concentrate on three issues from the viewpoint of service-robot applications. The first issue is to estimate kinematic parameters by using an active-sensing strategy to overcome uncertainties in a real environment. The second issue is to provide an integrated strategy of motion coordination for door-opening control. This paper discusses the role assignment of each subsystem that depends on the physical characteristics. The third issue is to use the fingertip-contact forces to estimate the external force from a doorknob, instead of using an additional high-cost force sensor at the wrist. The proposed scheme is shown to be useful through experimental results. [ABSTRACT FROM AUTHOR]

In this paper, a method that makes biped robots track zero-moment-point (ZMP) reference trajectories is proposed. The biped robots have flat rectangular soles with force sensors at each corner. The sensors detect reaction force from the ground. Sensor information is transformed into useful structure, which is defined as "environmental modes." The environmental modes represent contact states between the ground and the soles and are extracted by the information of four force sensors at each corner of the rectangular soles. The environmental modes consist of the following four modes: 1) heaving; 2) rolling; 3) pitching; and 4) twisting. These modes are related to the ZMP, by which walking stability is evaluated. Therefore, command values of the environmental modes can be derived by the ZMP reference trajectory. By tracking the command values, the walking motion becomes more stable. The conventional study on controlling the environmental modes takes only the rolling and pitching modes into account. However, it is not sufficient to stabilize the walking motion, because the heaving mode has been neglected. The heaving mode is also very important to stabilize the walking motion. Therefore, in this paper, we extend the conventional method for considering the heaving mode to track the ZMP reference trajectory. Validity of the proposed method was confirmed by experimental results. [ABSTRACT FROM AUTHOR]

This paper presents a methodology for the compensation of nonlinear friction in a robot joint structure based on a fuzzy local modeling technique. To enhance the tracking performance of the robot joint, a dynamic model is derived from the local physical properties of friction. The model is the basis of a precompensator taking into account the dynamics of the overall corrected system by means of a minor loop. The proposed structure does not claim to faithfully reproduce complex phenomena driven by friction. However, the linearity of the local models simplifies the design and implementation of the observer, and its estimation capabilities are improved by the nonlinear integral gain. The controller can then be robustly synthesized using linear matrix inequalities to cancel the effects of inexact friction compensation. Experimental tests conducted on a robot joint with a high level of friction demonstrate the effectiveness of the proposed fuzzy observer-based control strategy for tracking system trajectories when operating in zero-velocity regions and during motion reversals. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach to the modeling and identification of elastic robot joints with hysteresis and backlash. The model captures the dynamic behavior of a rigid robotic manipulator with elastic joints. The model includes electromechanical submodels of the motor and gear from which the relationship between the applied torque and the joint torsion is identified. The friction behavior in both presliding and sliding regimes is captured by Generalized Maxwell-Slip model. The hysteresis is described by a Preisach operator. The distributed model parameters are identified from experimental data obtained from internal system signals and external angular encoder mounted to the second joint of a 6-DOF industrial robot. The validity of the identified model is confirmed by the agreement of its prediction with independent experimental data not previously used for model identification. The obtained models open an avenue for future advanced high-precision control of robotic manipulator dynamics. [ABSTRACT FROM AUTHOR]

This paper proposes a tactile-sensing mechanism for a robot. The mechanism is composed of a force-sensor device and an end-effector of shell shape. Since the end-effector plays the role o an outer shell, a force can be sensed, at any position on the body. Due to the aspect of its intrinsic contact sensing, position of the single contact point is calculable without any sensor array. Another advantage is that the six-axis resultant force is measurable. This paper shows that the mechanism is also available for the end-effector with an angulated shape. The only condition for the shape is to be a convex hull. Some experimental results evaluate sources of error in practical measurement and show the validity of the proposed mechanism. [ABSTRACT FROM AUTHOR]

Robots working in the human environment have been researched in the field of motion control. For the next-generation robot, human and robot interaction technologies are needed. In particular, learning and displaying of human haptic motion are important. Therefore, the authors have proposed a method for abstracting haptic motion and designed a haptic motion display system. The motion abstraction method divides a measured motion to each action from the point of force and position. Then, action modes have been defined for expressing each divided action. Action modes are expressing force directionality or position directionality. By utilizing the proposed motion abstraction method, various kinds of human motion are abstracted as action modes. The designed haptic motion display system is trying to show these various kinds of human motion. This paper defines human action modes and environmental action modes from action modes. Human action modes are expressing human action force directionality, while environmental action modes are expressing environmental position response directionality. Furthermore, the haptic motion display system is redesigned. This system is redesigned based on human action modes and environmental action modes. The validity of the proposed method is confirmed by the experimental results. [ABSTRACT FROM AUTHOR]

The control of a biped humanoid is a challenging task due to the hard-to-stabilize dynamics. Walking reference trajectory generation is a key problem. Linear Inverted Pendulum Model (LIPM) and Zero Moment Point (ZMP) Criterion-based approaches in stable walking reference generation are reported. In these methods, generally, the ZMP reference during a stepping motion is kept fixed in the middle of the supporting foot sole. This kind of reference generation lacks naturalness, in that the ZMP in the human walk does not stay fixed, but it moves forward under the supporting foot. This paper proposes a reference generation algorithm based on the LIPM and moving support foot ZMP references. The application of Fourier series approximation simplifies the solution, and it generates a smooth ZMP reference. A simple inverse kinematics-based joint space controller is used for the tests of the developed reference trajectory through full-dynamics 3-D simulation. A 12-DOF biped robot model is used in the simulations. Simulation studies suggest that the moving ZMP references are more energy efficient than the ones with fixed ZMP under the supporting foot. The results are promising for implementations. [ABSTRACT FROM AUTHOR]

The navigation for a car-like wheeled robot (CLWR) in a distributed active-vision network-space system (DAVNSS) subject to three fuzzy variable-structure decentralized controls (FVSDC5) is developed. The scheme also includes trajectory tracking and obstacle avoidance. Two distributed wireless charge- coupled-device (CCD) cameras individually driven by two stepping motors, viz., active CCD1 and active CCD2 (or simply ACCD1 and ACCD2), are constructed to capture the dynamic pose of the CLWR and the obstacle. The proposed control system includes quad processors with multiple sampling rates. First, a personal computer (PC) is employed to receive the image of the CLWR or obstacle from ACCD1 or ACCD2 by a wireless transmitter and then to plan three reference commands for CLWR, ACCD1, and ACCD2. Next, a six-step image-processing routine and the calibration between the world coordinate and the image plane coordinate using multilayer perceptrons (MLPs) are established. Finally, experiments are performed to validate the proposed control system. [ABSTRACT FROM AUTHOR]

As robotic systems are becoming more complex, distributed, and integrated, there is the need to build sophisticated frameworks to embody intelligence in the robot. This paper presents a component-based software architecture for the integration of industrial robotic platforms with multisensor systems where data fusion is relevant. The architecture is based on an open software robotic platform that is able to fulfill capabilities such as openness, interoperability, adaptability, and modularity, with the addition of hardware in the loop simulator. The resulting robot platform permits easy implementation of model- and sensor-based control concepts, proving to be interesting for robotics research. In addition, it allows the integration of standard industrial components. The entire system has been successfully developed, implemented, and demonstrated for robotic tasks, where multiple and different sensors are required. [ABSTRACT FROM AUTHOR]

This paper describes a novel bilateral grasping control system including master-slave robots with different degree of freedom. The master and slave controllers are designed based on a multilateral control scheme. Decoupling design of force and position controllers is realized by mode transformation using the discrete Fourier transform matrices and a disturbance observer. In the proposed system, a human operator manipulates two master robots, and three slave robots grasp an object cooperatively. The proposed system makes it possible to grasp an object tightly in the slave side and to transmit feeling of grasping to a human operator vividly. The validity of the proposed method is shown by numerical and experimental results. [ABSTRACT FROM AUTHOR]

In light of the remarkable benefits and numerous applications of the Takagi-Sugeno (T-S) fuzzy system modeling method and the sliding mode control (SMC) technique, this paper aims to study the design of robust controllers for a set of second-order systems using a combination of these two approaches. The combined scheme is shown to have the merits of both approaches. It alleviates not only the online computational burden by using the T-S fuzzy system model to approximate the original nonlinear one (since most of the system parameters of the T-S model can be computed offline) but also preserves the advantages of rapid response and robustness characteristic of the classic SMC schemes. Moreover, the combined scheme does not need to online compute any nonlinear term of the original dynamics, and the increase in the number of fuzzy rules does not create extra online computational burdens for the scheme. The proposed analytical results are also applied to the control of a two-link robot manipulator and compared with the results using classic SMC design. Simulation results demonstrate the benefits of the proposed scheme. [ABSTRACT FROM AUTHOR]

The constructive need for robots to coexist with humans requires human-machine interaction. It is a challenge to operate these robots in such dynamic environments, which requires continuous decision-making and environment-attribute update in real-time. An autonomous robot guide is well suitable in places such as museums, libraries, schools, hospital, etc. This paper addresses a scenario where a robot tracks and follows a human. A neural network is utilized to learn the skin and nonskin colors. The skin-color probability map is utilized for skin classification and morphology-based preprocessing. Heuristic rule is used for face-ratio analysis and Bayesian cost analysis for label classification. A face-detection module, based on a 2-D color model in the YCrCb and YUV color space, is selected over the traditional skin-color model in a 3-D color space. A modified Continuously Adaptive Mean Shift tracking mechanism in a 1-D Hue, Saturation, and Value color space is developed and implemented onto the mobile robot. In addition to the visual cues, the tracking process considers 16 sonar scan and tactile sensor readings from the robot to generate a robust measure of the person's distance from the robot. The robot thus decides an appropriate action, namely, to follow the human subject and perform obstacle avoidance. The proposed approach is orientation invariant under varying lighting conditions and invariant to natural transformations such as translation, rotation, and scaling. Such a multimodal solution is effective for face detection and tracking. [ABSTRACT FROM AUTHOR]

This paper presents a new approach for compliance control using a traveling-wave ultrasonic motor. Its objective is to demonstrate the effectiveness of using duty ratios and frequencies as control variables for both preload and stiffness control. At the home position, the motor is engaged in a standing-wave mode operation and provides self-locking torque. When the motor is deflected, it is engaged in a traveling-wave mode operation to provide a reacting torque. The torque is varied according to the deflection to provide the desired stiffness. Experiments have confirmed the effectiveness of this method. This approach can also be readily deployed into many force-feedback and haptic applications such as robotic locomotion. [ABSTRACT FROM AUTHOR]

A simple robust compliant-motion-control technique is presented for a robot manipulator with nonlinear friction. The control technique incorporates both time-delay-estimation technique and ideal velocity feedback; the former is used to cancel out soft nonlinearities, and the latter serves to reduce the effect of hard nonlinearities, including Coulomb friction and stiction. The proposed controller has a simple structure and yet provides good online friction compensation without modeling friction. The robustness of the proposed method has been confirmed through comparisons with other controllers in 2-DOF SCARA-type industrial robot experiments. [ABSTRACT FROM AUTHOR]

Robots are expected to expand their range of activities to human environment. Robots in human environment need redundancy for environmental adaptation. Furthermore, they have to automatically modify their controllers in response to varying conditions of the environment. Therefore, the authors have proposed a method to design a hyper-degrees-of-freedom (DOF) control system efficiently. The method decouples a large control system into small independent components called "function." Motion of the entire control system is expressed as superposition of multiple functions. Combination of some functions realizes many patterns of motion. Hence, various motions are realized with much smaller efforts on controller design. Additionally, the controller design is explicit since a controller and a function correspond directly. This paper expands the method to multi-DOF robots in 3-D space, since the conventional method was limited to a multirobot system in 1-D space. A new problem of interference among function-based systems occurs along with the expansion. A disturbance observer is applied on each actuator to eliminate the interference. Procedures of controller design under varying conditions are also shown. The proposed method is applied to a grasping manipulator with 18 DOF. Its experimental results show the validity of the method. [ABSTRACT FROM AUTHOR]

Experimentation and practical work, which are usually accomplished in a laboratory, are the basics of technological fields. Laboratory activities enable students to acquire methodologies, work habits, knowledge, and experience of equipment operation, in conditions as near as possible to their future professional activities. The evolution of communication and information technologies opens new possibilities in educational methods. This article describes a project that aims to facilitate the use of real robots in an educational laboratory via Web, allowing users to learn different robotics aspects while performing a competition. Students can remotely program several robots to participate in games to accomplish a set of goals in a remote stadium (the RoboStadium). To facilitate the use of robots, the online robot stadium provides a set of training resources. Having these resources, previous knowledge on robotics is not required to use the system. Since robotics is a multidisciplinary field (mechanics, electronics, control, mathematics, computers, etc.), students of different degrees can take advantage of the presented system. Researchers of two Spanish universities are participating in this project, which provides robotics telelaboratories via Web. [ABSTRACT FROM AUTHOR]

Motion control technology in an open environment will be more important. Future motion systems should interact with other systems or environments. To adapt to complicated environments and do tasks, a realization of multi-degree-of-freedom motion is necessary for human cooperating motion. This paper proposes a unified control approach for multirobot systems by interaction mode control. The proposed interaction mode control considers only interactions between systems. The interactions are abstracted by using mode quarry matrices. Since the transformed modes are independent of each other, it is possible to design a controller in decoupled modal space. This paper also proposes a novel control index named "hybrid ratio." Hybrid ratio is defined as the influence of external acceleration input on the acceleration response of a system. Since it is possible to realize the assigned hybrid ratio in each mode according to the task, the motion command with hybrid ratio is represented as task code. Thus, the interaction mode control is able to be treated as task kinematics. The proposed interaction mode control is applied for grasping motion by multirobot systems. The numerical and experimental results show the viability of the proposed method. [ABSTRACT FROM AUTHOR]

Almost all present control strategies for electrically driven robots are under the rigid robot assumption. Few results can be found for the control of electrically driven robots with joint flexibility. This is because the presence of the joint flexibility greatly increases the complexity of the system dynamics. What is worse is when some system dynamics are not available and a good performance controller is required. In this paper, an adaptive design is proposed to this challenging problem. A backstepping-like procedure incorporating the model reference adaptive control is employed to circumvent the difficulty introduced by its cascade structure and various uncertainties. A Lyapunov-like analysis is used to justify the closed-loop stability and boundedness of internal signals. Computer simulation results are presented to demonstrate the usefulness of the proposed scheme. [ABSTRACT FROM AUTHOR]