In this paper, a novel control scheme is developed for teleoperation system, combining the radial basis function (RBF) neural networks (NNs) and wave variable technique to simultaneously compensate effects caused by communication delays dynamics uncertainties. The system set up with TouchX joystick as master device simulated Baxter robot arm slave robot. haptic feedback provided human operator sense interaction force between environment when manipulating stylus of joystick. To utilize...

In this paper, adaptive impedance control is proposed for a robot collaborating with human partner, in the presence of unknown motion intention partner and dynamics. Human defined as desired trajectory limb model which extremely difficult to obtain considering nonlinear time-varying property model. Neural networks are employed cope problem, based on an online estimation method developed. The estimated integrated into developed control, makes follow given target Under method, able actively...

In this paper, an admittance adaptation method has been developed for robots to interact with unknown environments. The environment be interacted is modeled as a linear system. the presence of dynamics environments, observer in robot joint space employed estimate interaction torque, and control adopted regulate behavior at points. An adaptive neural controller using radial basis function guarantee trajectory tracking. A cost that defines performance torque regulation tracking minimized by...

Humans can skilfully use tools and interact with the environment by adapting their movement trajectory, contact force, impedance. Motivated human versatility, we develop here a robot controller that concurrently adapts feedforward impedance, reference trajectory when interacting an unknown environment. In particular, robot's is adapted to limit interaction force maintain it at desired level, while impedance adaptation compensates for An analysis of dynamics using Lyapunov theory yields...

In this paper, impedance learning is investigated for robots interacting with unknown environments. A two-loop control framework employed and adaptive developed the inner-loop position control. The environments are described as time-varying systems parameters in state-space form. gradient-following betterment schemes to obtain a desired model, subject interaction performance achieved sense that defined cost function minimized. Simulation experiment studies carried out verify validity of...

In this article, we propose a hybrid framework using visual and force sensing for human-robot co-carrying tasks. Visual is utilized to obtain human motion an observer designed estimating control input of human, which generates robot's desired toward human's intended motion. An adaptive impedance-based strategy proposed trajectory tracking with neural networks used compensate uncertainties in dynamics. Motion synchronization achieved approach yields stable efficient interaction behavior...

Mobile robots can complete a task in cooperation with human partner. In this letter, hybrid shared control method for mobile robot omnidirectional wheels is proposed. A partner utilizes six degrees of freedom haptic device and electromyography (EMG) signals sensor to the robot. approach based on EMG artificial potential field exploited avoid obstacles according repulsive force attractive enhance perception remote environment feedback platform. This enables tele-control robot's motion achieve...

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...

In this paper, we propose a framework to analyze the interactive behaviors of human and robot in physical interactions.Game theory is employed describe system under study, policy iteration adopted provide solution Nash equilibrium.The human's control objective estimated based on measured interaction force, it used adapt robot's such that human-robot coordination can be achieved.The validity proposed method verified through rigorous proof experimental studies.

Transferring human stiffness regulation strategies to robots enables them effectively and efficiently acquire adaptive impedance control policies deal with uncertainties during the accomplishment of physical contact tasks in an unstructured environment. In this article, we develop such a human-robot interaction system which allows learn variable skills from demonstrations. Specifically, biological signals, i.e., surface electromyography are utilized for extraction arm features task...

In this work, a human motion intention prediction method based on an autoregressive (AR) model for teleoperation is developed. Based method, the robot's trajectory can be updated in real time through updating parameters of AR model. teleoperated control loop, virtual force defined to describe interaction profile and correct time. The proposed algorithm acts as feedforward update revise process human–robot (HRI). convergence analyzed theoretically. Comparative studies demonstrate enhanced...

Finite/fixed-time control yields a promising tool to optimize system's settling time, but lacks the ability separately define time and convergence domain (known as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">practically prescribed-time stability</i> , PPTS). We provide sufficient condition for PPTS based on new piecewise exponential function, which decouples into user-defined parameters. propose an adaptive event-triggered scheme...

In this article, learning impedance control is proposed for physical robot–environment interaction. Learning mechanism developed such that the knowledge of robot structure not required. With method, dynamics arm governed to follow a target model and interaction objective achieved. The performance discussed through rigorous analysis. validity method verified by simulation studies.

In this paper, the formation tracking control is studied for a multiagent system (MAS) with communication limitations. The objective to group of agents track desired trajectory while maintaining given in nonomniscient constrained space. role switching triggered by detection unexpected spatial constraints facilitates efficiency event-triggered bandwidth, energy consumption, and processor usage. A coordination mechanism proposed based on novel "coordinator" indirectly spread environmental...

As a typical smart structure, the piezoelectric actuator (PEA) is an essential constituent component in piezoelectric-driven positioning stages. Nevertheless, precision severely degraded by its innate rate-dependent hysteretic nonlinearity. In this article, innovative control method which combines active disturbance rejection (ADRC) and current-cycle iterative learning (CILC) proposed constructing PEA as second-order disturbance-based structure to handle both nonlinearities dynamic...

It is widely acknowledged that drivers should remain in the control loop before automated vehicles completely meet real-world operational conditions. This paper presents an "indirect shared control" framework for steer-by-wire vehicles, which allows authority to be continuously between driver and automation through weighted-input-summation method. A "best-response" steering model based on predictive (MPC) indirect proposed. Unlike any conventional manual driving, this assumes can learn...

In this paper, we present an adaptive control of robotic manipulators with parametric uncertainties and motion constraints. Position velocity constraints are considered they unified converted into the constraint nominal input. An neural network is developed to achieve trajectory tracking, while problems addressed by considering saturation effect The uniform boundedness all closed-loop signals verified through Lyapunov analysis. Simulation experiment results on a 2-degree-of-freedom...