A5086990393- Robot Manipulation and Learning
- Adaptive Control of Nonlinear Systems
- Prosthetics and Rehabilitation Robotics
- Teleoperation and Haptic Systems
- Muscle activation and electromyography studies
- Control and Dynamics of Mobile Robots
- Fuzzy Logic and Control Systems
- Fault Detection and Control Systems
- Distributed Control Multi-Agent Systems
- Human-Automation Interaction and Safety
- Advanced Control Systems Design
- Iterative Learning Control Systems
- Hydraulic and Pneumatic Systems
- Soft Robotics and Applications
University of Science and Technology Beijing
2019-2020
Southeast University
2018
In this article, an admittance-based controller for physical human-robot interaction (pHRI) is presented to perform the coordinated operation in constrained task space. An admittance model and a soft saturation function are employed generate differentiable reference trajectory ensure that end-effector motion of manipulator complies with human avoids collision surroundings. Then, adaptive neural network (NN) involving integral barrier Lyapunov (IBLF) designed deal tracking issues. Meanwhile,...
This article proposes a Bayesian method to acquire the estimation of human impedance and motion intention in human–robot collaborative task. Combining with prior knowledge stiffness, estimated stiffness obeying Gaussian distribution is obtained by estimation, can be also estimated. An adaptive control strategy employed track target model neural networks are used compensate for uncertainties robotic dynamics. Comparative simulation results carried out verify effectiveness emphasize advantages...
Purpose This paper aims to propose cooperative control strategies for dual-arm robots in different human–robot collaborative tasks assembly processes. The authors set three regions where robot performs ways: “teleoperate” region, “co-carry” region and “assembly” region. Human holds the “master” arm of operate other “follower” by our proposed controller “teleoperation” Limited human length, is teleoperated carry distant object. In cooperatively object close human. used fixing coupled with...
In this paper, a fuzzy logic control strategy is proposed for solving trajectory tracking issues of an uncertain manipulator. Fuzzy utilized to compensate nonlinear uncertainties in manipulator dynamics and full-state constraints are involved feedback controller design ensuring motion during movement processes. Disturbance observer (DO) designed counteract the effects unknown disturbances caused by friction force or other various forms disturbance. Combining with Lyapunov theory...
This paper proposes a finite-time neural impedance control for robotic manipulator. A position-based controller is proposed to improve the safety and compliance when manipulator contacts with environment physically. Radial basis functions networks (RBFNNs) are employed compensate uncertainties in dynamics. method developed back-stepping technique tracking performance. Large external forces can be avoided desired model achieved quickly under our method. The stability close-loop system proven...
This paper proposed an adaptive neural admittance control strategy for collision avoidance in human-robot collaborative tasks. In order to ensure that the robot end-effector can avoid collisions with surroundings, should be operated compliantly by human within a constrained task space. An impedance model and soft saturation function are employed generate differentiable reference trajectory. Then, network position constraint, based on integral barrier Lyapunov (IBLF), is designed achieve...
In this paper, a fuzzy logic control strategy is proposed for solving trajectory tracking issues of an uncertain manipulator. Fuzzy utilized to compensate manipulator dynamics uncertainties and full-state constraints are involved in feedback controller design. The method can guarantee error signals closed-loop system semi-globally uniformly bounded (SGUB). view safe operation, tangent barrier Lyapunov functions (tBLFs) chosen maintain full states predefined constrained region processes....