All Outputs (107)

Trajectory online adaption based on human motion prediction for teleoperation (2021)
Journal Article

In this work, a human motion intention prediction method based on an autoregressive (AR) model for teleoperation is developed. Based on this method, the robot's motion trajectory can be updated in real time through updating the parameters of the AR m... Read More about Trajectory online adaption based on human motion prediction for teleoperation.

An improvement of robot stiffness-adaptive skill primitive generalization using the surface electromyography in human–robot collaboration (2021)
Journal Article

Learning from Demonstration in robotics has proved its efficiency in robot skill learning. The generalization goals of most skill expression models in real scenarios are specified by humans or associated with other perceptual data. Our proposed frame... Read More about An improvement of robot stiffness-adaptive skill primitive generalization using the surface electromyography in human–robot collaboration.

Adaptive neural control of a class of uncertain state and input-delayed systems with input magnitude and rate constraints (2021)
Journal Article

This article aims at proposing an adaptive neural control strategy for a class of nonlinear time-delay systems with input delays and unknown control directions. Different from previous researches that investigated delays and constraints separately, t... Read More about Adaptive neural control of a class of uncertain state and input-delayed systems with input magnitude and rate constraints.

A novel iterative identification based on the optimised topology for common state monitoring in wireless sensor networks (2021)
Journal Article

Power consumption and data redundancy of wireless sensor networks (WSN) are widely considered for a distributed state monitoring network. For reducing the energy consumption and data amount, we propose a topology optimisation and an iterative paramet... Read More about A novel iterative identification based on the optimised topology for common state monitoring in wireless sensor networks.

Review of the techniques used in motor‐cognitive human‐robot skill transfer (2021)
Journal Article

A conventional robot programming method extensively limits the reusability of skills in the developmental aspect. Engineers programme a robot in a targeted manner for the realisation of predefined skills. The low reusability of general-purpose robot... Read More about Review of the techniques used in motor‐cognitive human‐robot skill transfer.

Robot learning system based on dynamic movement primitives and neural network (2021)
Journal Article

In the process of Human-robot skill transfer, we require the robot to reproduce the trajectory of teacher and expect that the robot can generalize the learned trajectory. For the trajectory after generalization, we expect that the robot arm can accur... Read More about Robot learning system based on dynamic movement primitives and neural network.

A review on manipulation skill acquisition through teleoperation‐based learning from demonstration (2021)
Journal Article

Manipulation skill learning and generalisation have gained increasing attention due to the wide applications of robot manipulators and the spurt of robot learning techniques. Especially, the learning from demonstration method has been exploited widel... Read More about A review on manipulation skill acquisition through teleoperation‐based learning from demonstration.

Distributed cooperative kinematic control of multiple robotic manipulators with improved communication efficiency (2021)
Journal Article

An efficiency-oriented solution is theoretically a preferred choice to support the efficient operation of a system. Although some studies on the multi-manipulator system share the load of the control center by transforming the network topology, the w... Read More about Distributed cooperative kinematic control of multiple robotic manipulators with improved communication efficiency.

Composite dynamic movement primitives based on neural networks for human–robot skill transfer (2021)
Journal Article

In this paper, composite dynamic movement primitives (DMPs) based on radial basis function neural networks (RBFNNs) are investigated for robots’ skill learning from human demonstrations. The composite DMPs could encode the position and orientation ma... Read More about Composite dynamic movement primitives based on neural networks for human–robot skill transfer.

A constrained DMPs framework for robot skills learning and generalization from human demonstrations (2021)
Journal Article

Dynamical movement primitives (DMPs) model is a useful tool for efficiently robotic learning manipulation skills from human demonstrations and then generalizing these skills to fulfill new tasks. It is improved and applied for the cases with multiple... Read More about A constrained DMPs framework for robot skills learning and generalization from human demonstrations.

Learning compliant robotic movements based on biomimetic motor adaptation (2020)
Journal Article

It is one of the great challenges for a robot to learn compliant movements in interaction tasks. The robot can easily acquire motion skills from a human tutor by kinematics demonstration, however, this becomes much more difficult when it comes to the... Read More about Learning compliant robotic movements based on biomimetic motor adaptation.

Robust neurooptimal control for a robot via adaptive dynamic programming (2020)
Journal Article

We aim at the optimization of the tracking control of a robot to improve the robustness, under the effect of unknown nonlinear perturbations. First, an auxiliary system is introduced, and optimal control of the auxiliary system can be seen as an appr... Read More about Robust neurooptimal control for a robot via adaptive dynamic programming.

Recent advances in robot-assisted echography: Combining perception, control and cognition (2020)
Journal Article

Echography imaging is an important technique frequently used in medical diagnostics due to low-cost, non-ionising characteristics, and pragmatic convenience. Due to the shortage of skilful technicians and injuries of physicians sustained from diagnos... Read More about Recent advances in robot-assisted echography: Combining perception, control and cognition.

An incremental learning framework to enhance teaching by demonstration based on multimodal sensor fusion (2020)
Journal Article

Though a robot can reproduce the demonstration trajectory from a human demonstrator by teleoperation, there is a certain error between the reproduced trajectory and the desired trajectory. To minimize this error, we propose a multimodal incremental l... Read More about An incremental learning framework to enhance teaching by demonstration based on multimodal sensor fusion.

Disturbance observer enhanced variable gain controller for robot teleoperation with motion capture using wearable armbands (2020)
Journal Article

Disturbance observer (DOB) based controller performs well in estimating and compensating for perturbation when the external or internal unknown disturbance is slowly time varying. However, to some extent, robot manipulators usually work in complex en... Read More about Disturbance observer enhanced variable gain controller for robot teleoperation with motion capture using wearable armbands.

Novel joint-drift-free scheme at acceleration level for robotic redundancy resolution with tracking error theoretically eliminated (2020)
Journal Article

In this article, three acceleration-level joint-drift-free (ALJDF) schemes for kinematic control of redundant manipulators are proposed and analyzed from perspectives of dynamics and kinematics with the corresponding tracking error analyses. First, t... Read More about Novel joint-drift-free scheme at acceleration level for robotic redundancy resolution with tracking error theoretically eliminated.

Neural-learning-based force sensorless admittance control for robots with input deadzone (2020)
Journal Article

This paper presents a neural networks based admittance control scheme for robotic manipulators when interacting with the unknown environment in the presence of the actuator deadzone without needing force sensing. A compliant behaviour of robotic mani... Read More about Neural-learning-based force sensorless admittance control for robots with input deadzone.

Adaptive dynamic programming-based controller with admittance adaptation for robot–environment interaction (2020)
Journal Article

The problem of optimal tracking control for robot–environment interaction is studied in this article. The environment is regarded as a linear system and an admittance control with iterative linear quadratic regulator method is obtained to guarantee t... Read More about Adaptive dynamic programming-based controller with admittance adaptation for robot–environment interaction.

Disturbance observer-based fault-tolerant control for robotic systems with guaranteed prescribed performance (2020)
Journal Article

The actuator failure compensation control problem of robotic systems possessing dynamic uncertainties has been investigated in this paper. Control design against partial loss of effectiveness (PLOE) and total loss of effectiveness (TLOE) of the actua... Read More about Disturbance observer-based fault-tolerant control for robotic systems with guaranteed prescribed performance.

Biologically inspired deadbeat control of robotic leg prostheses (2020)
Journal Article

Recent advances in robotics technology provide great support for robotic leg prostheses to realize full biomechanical functionalities of the contralateral leg. In order to reproduce the biomechanical behaviors of the contralateral leg, this article a... Read More about Biologically inspired deadbeat control of robotic leg prostheses.