Narrow Results

Uncertainty in the master–slave model is one of the primary factors affecting the transparency of teleoperation systems, and congestion in the master–slave communication network also greatly influences the performance of the teleoperation system. This paper proposes a combined framework of adaptive and impedance control to address the uncertainty in the master–slave model and achieve smooth operation at the slave end. Building upon this linear model, an event-triggered mechanism is designed using Lyapunov functions, with dynamic online adjustment of the triggering threshold parameters. Following the completion of the aforementioned research, control objectives are established to validate the performance of the teleoperation control system proposed in this paper. Finally, simulation verification is conducted in the Matlab/Simulink environment.

An adaptive impedance control method based on dexterity for compliant interaction is proposed for the problem of compliance and motion performance of the human’s healthy side interacting with the manipulator in bilateral mirror rehabilitation motion-assisted training, and constructs a local virtual force field to hinder the movement of the manipulator to the low motion performance region, thus improving the motion performance of the manipulator. Firstly, the dynamic model of the manipulator and the human–robot interaction model based on impedance control are established. Then, a dexterity index based on the condition number is established, and an adaptive impedance control method based on the dexterity is proposed to construct a local virtual force field to hinder the movement of the manipulator to the low motion performance region. Finally, the effectiveness of the proposed method is demonstrated by experiments. The results have shown that the adaptive impedance control method based on dexterity can construct a local virtual force field, which can constrain the motion of the manipulator and keep the robot with good motion performance. It also laid the foundation for the training strategy of bilateral mirror rehabilitation.

In this study, a wearable exoskeleton with an active drive mechanism was designed for both space-saving and to ensure the safety and comfort of the workers. At the same time, this active wearable exoskeleton mechanism aims to facilitate the daily life of disabled people with its movement assisting feature. For these purposes, an active and wearable exoskeleton with a total of five degrees of freedom, two active (arm and shoulder flexion/extension) and three passive axes (shoulder lateral rotation and shoulder abduction/adduction), was developed. A novel load suspension system has been implemented to the design for absorbtion of the mechanism’s own weight. The force-based impedance control method has been used for effective human–robot interaction. Furthermore, a low-cost electromyography sensor has been developed and integrated into the robotic system as biological feedback. As a result of the tests, it has been revealed that the system can help with lifting loads and successfully perform rehabilitation exercises.

Parallel robots have been found in many applications where the work requirements are beyond the capabilities of serial robots. For example, mouth movements of chewing foods can be generated by a parallel robot. In this paper, the issue of dynamic position and force control of a chewing robot with a 6RSS mechanism is addressed. The kinematic and dynamic models of a generic 6RSS robot are developed and are then simplified considering the special features of a practical chewing robot and the requirements of controller design. An impedance control scheme is proposed to achieve the position and force control of the robot. A detailed description on the steps to implement the controller is also presented.

This paper presents impedance controllers with adaptive friction compensation for the five-finger dexterous robot hand DLR-HIT II in both joint and Cartesian space. An FPGA-based control hardware and software architecture with real-time communication is designed to fulfill the requirements of the impedance controller. Modeling of the robot finger with flexible joints and mechanical couplings in the differential gear-box are described in this paper. In order to address the friction due to the complex transmission system and joint coupling, an adaptive model-based friction estimation method is carried out with an extended Kalman filter. The performance of the impedance controller with both adaptive and parameter-fixed friction compensations for the robot hand DLR-HIT II are analyzed and compared in this paper. Furthermore, gravity estimation is implemented with Least Squares technique to address uncertainties in gravity compensation due to the close proximity and complexity of robot hand components. Experimental results prove that accurate position tracking and stable torque/force response can be achieved with the proposed impedance controller with friction compensation on five-finger dexterous robot hand DLR-HIT II.

As whole-body control approaches begin to enter the mainstream of humanoid robotics research, there is a real need to address the challenges and pitfalls encountered in hardware implementations. This paper presents an optimization-based whole-body control framework enabling compliant locomotion on THOR, a 34 degree of freedom humanoid featuring force-controllable series elastic actuators (SEAs). Given desired momentum rates of change, end-effector accelerations, and joint accelerations from a high-level locomotion controller, joint torque setpoints are computed using an efficient quadratic program (QP) formulation designed to solve the floating-base inverse dynamics (ID). Constraints on the centroidal dynamics, frictional contact forces, and joint position/torque limits ensure admissibility of the optimized joint setpoints. The control approach is supported by an electromechanical design that relies on custom linear SEAs and embedded joint controllers to accurately regulate the internal and external forces computed by the whole-body QP. Push recovery and walking tests conducted using the THOR humanoid validate the effectiveness of the proposed approach. In each case, balancing is achieved using a planning and control approach based on the time-varying divergent component of motion (DCM) implemented for the first time on hardware. We discuss practical considerations that led to the successful implementation of low-impedance whole-body control on our hardware system including the design of the robot’s high-level standing and stepping behaviors and low-level joint-space controllers. The paper concludes with an application of the presented approach for a humanoid firefighting demonstration onboard a decommissioned US Navy ship.

A new hybrid joystick has been developed to share the six degrees of freedom (DOF) by three DOF inputs and three DOF feedback signals. For remotely controlling a mobile robot, steering and acceleration commands can be generated by a 3-DOF joystick using $x$, $y$, and $z$ directional motions, respectively. Usually, a remote operator cannot clearly watch dynamically changing terrain conditions; therefore, it is necessary to feedback the slope and tilt conditions of the road to the operator through the joystick. These values can be obtained based on the inertial navigation system (INS) and feedback to the joystick as kind of reflection forces. Further, a yaw angle has been used to feedback the actual direction of the robot through a steering control. The mechanism and control systems of the hybrid joystick are newly designed, and the effectiveness of this hybrid joystick has been verified through actual remote operation of a mobile robot driving on slanted and tilted terrain.

Compared with the traditional hydraulic humanoid robots, the WLR-II, a novel hydraulic wheel-legged robot developed by using hose-less design, can significantly increase the reliability and maneuverability. The WLR-II combines the rough-terrain capability of legs with the efficiency of wheels. In this paper, a novel framework called rough-terrain adaption framework (RTAF) is presented which allows WLR-II to move on both flat terrains and terrains with unmodeled contact dynamics. RTAF is a hierarchical framework, which has a high-level balance controller and a low-level impedance controller that a high-performance nested torque controller with feed-forward velocity compensation is used. The low-level impedance controller for the hydraulic-driven unit can cancel out the load dynamics influence such as unexpected terrain disturbances and increase the force-tracking performance. With the high-level balance controller, the robot is able to handle unexpected terrain disturbances through wheel-ground force estimation, pitch/roll balance control and impedance parameter regulator. The proposed approach is suitable for a wheel-legged humanoid robot to manage balance through torque control at joints and regulate force-based interaction on rough terrains. The performance of the proposed RTAF is evaluated on variable gradient slopes and grassland which are the typical rough-terrain scenarios for real-world applications. The experimental results reveal that the maximum speed of grassland movement can reach 3 km/h.

In this paper, the application of a robotic arm for needle-based medical interventions under a preoperative CT-scan is investigated. The proposed setup consists of a robot manipulator with a customized needle guide mounted on its end-effector. A workflow that considers all the issues related to the registration and needle positioning algorithms is proposed. The so-called constrained admittance control approach is proposed to provide semi-autonomous positioning of the needle guide on the target path based on CT-scan images. The proposed algorithms are verified experimentally through phantom studies.

Robot-assisted arthroscopic surgery has been receiving growing attention in the field of orthopedic surgery. Most of the existing robot-assisted surgical systems in orthopedics place more focus on open surgery than minimally invasive surgery (MIS). In traditional arthroscopic surgery, the surgeon needs to hold an arthroscope with one hand while performing the surgical operations with the other hand, which can restrict the dexterity of the surgical performance and increase the cognitive load. On the other hand, the surgeon heavily relies on the arthroscope view when conducting the surgery, whereas the arthroscope view is a largely localized view and lacks depth information. To assist the surgeon in both scenarios, in this work, we develop a two-arm robotic system. The left-arm robot is used as a robot-assisted arthroscope holder, and it can hold the arthroscope still at a designated pose and reject all other potential disturbances, while also allowing the operator to move it via a pedal switch whenever needed. The left-arm robot is implemented with an impedance controller and a gravity iterative learning (Git) scheme, where the former can provide compliant robot behavior, thus ensuring a safe human–robot interaction, while the latter can accurately learn for gravity compensation. The right-arm robot is used as a robot-assisted surgical tool, providing virtual fixture (VF) assistance and haptic feedback during the surgery. The right-arm robot is implemented with a point-based VF algorithm, which can generate VF directly from point clouds in any shape, render force feedback, and deliver it to the operator. Furthermore, the VF, the bone, and the surgical tool position are visualized in a 3D digital environment as additional visual feedback for the operator. A series of experiments are conducted to evaluate the effectiveness of the prototype. The results demonstrate that both arms can provide satisfactory assistance as designed.

To validate the principle of robot walking and manipulation in the future space tasks, a 7-DOF space robotic arm (SRA), its end effecter (EE) and grapple fixture (GF) were built. Also, a ground simulator was set up to provide a microgravity condition for the robot space grasping and walking tasks. We presented a Cartesian impedance control method for the SRA based on the feedback of a 6D force/torque sensor on the EE. Experiments proved the effectiveness and safety of the space walking robot and its ground simulator.

Empowering robotic solutions are exploited for industrial applications in order to reduce/limit risk factors related to musculoskeletal disorders (MSDs) and to improve the capabilities of humans. This paper aims at proposing both (a) the design and (b) the control of a cooperative manipulator in order to empower humans in onerous industrial tasks execution. (a) a dual driven actuation (DDA) is proposed and described for the shoulder joint of an empowering robotic system. (b) a fuzzy impedance control based approach to assist the human operator while lifting (partially) unknown weight components is proposed. The control method has been validated in a hatrack-like component installation, case-study related to the H2020 CleanSky 2 EURECA project. The proposed application has been shown during the KUKA Innovation Award. As a test platform, a KUKA iiwa 14 R820 has been used.

The success of an interaction control scheme is tightly related to the capacity of the actuators to follow the force references as much accurately as possible. The use of conventional actuators, usually modest at force control, lead to a inadequate performance of the interaction control system. This paper presents a leg prototype designed and developed for achieving agile locomotion. In the design, the selection of the proper actuation system has been a key issue for the development of the interaction control scheme. The HADE leg is actuated by means of three Series Elastic Actuators, and experimental results show the good performance of the impedance control performed with these actuators.

Bioinspired legged robots are a good option for field missions over complex terrain such as extraterrestrial landscape, disaster scenarios, etc. For these applications robots should exhibit good performance in terms of mobility, payload and endurance. In this work a control law to exploit the HADE leg dynamic features in order to save electrical energy by reducing the required mechanical work is presented. This control law is a force based impedance control scheme that considers the fact that the prototype is an underactuated mechanism. An analysis on the energy saving capabilities of the system, based on spring stiffness is theoretically performed and experimentally validated.

In recent years the robotics community has focused its interest on the control of the impedance of compliant actuators to increase safety and to make the interaction with humans more natural. Biological systems are elastic and are able to modulate joint impedance while keeping stability through co-activation and reciprocal activation of muscles. In order to implement a bio-equivalent, technical drive actuation system for prosthetics, a bio-inspired position and stiffness control strategy has been implemented and connected to a technical model of an elbow joint. The sum of all muscle–torques actuating the joint represents the net-torque that should be generated in the technical elbow to realize the desired motion. This net-torque is transmitted to a miniaturized lightweight joint drive with inherent serial elasticity and controlled with a speed–torque control cascade. The impedance range of the biological musculoskeletal system is evaluated in simulation and compared to the range obtained when the technical drive is acting instead of its biological counterpart. The impedance range of the technical drive using biological controllers is equivalent to that achieved in the biological example. Simulation results of the biologically controlled drive for different load situations show that the system successfully modulates impedance both in static cases and during movements while keeping stability.

As an auxiliary treatment, the 6-DOF parallel robot plays an important role in lower limb rehabilitation. In order to improve the efficiency and flexibility of the lower limb rehabilitation training, this paper studies the impedance controller based on the position control. A nonsingular terminal sliding mode control is developed to ensure the trajectory tracking precision and in contrast to traditional PID control strategy in the inner position loop, the system will be more stable. The stability of the system is proved by Lyapunov function to guarantee the convergence of the control errors. Simulation results validate the effectiveness of the target impedance model and show that the parallel robot can adjust gait trajectory online according to the human-machine interaction force to meet the gait request of patients, and changing the impedance parameters can meet the demands of different stages of rehabilitation training.