Human-Robot Interactive Control Sharing Same Workspace

2000 ◽  
Author(s):  
Jae Y. Lew ◽  
Yung-Tsan Jou ◽  
Hajrudin Pasic
Keyword(s):  
Feedback Control ◽  
Path Planning ◽  
Motion Planning ◽  
Simulation Study ◽  
Control Algorithm ◽  
Unexpected Events ◽  
Interactive Control ◽  
Control Scheme ◽  
Basic Motion

Abstract The paper presents a basic motion planning / feedback control algorithm for a robot working with a human in the same workspace. With the proposed control scheme, robots can be safe and easy to use when unexpected events occur. The algorithm is based on: (1) inertia reduction (2) passivity and (3) parametric path planning. A preliminary simulation study is performed to show its effectiveness with a two link manipulator.

Impedance Control: An Approach to Manipulation: Part III—Applications

1985 ◽  
Vol 107 (1) ◽  
pp. 17-24 ◽  
Author(s):  
Neville Hogan
Keyword(s):  
Feedback Control ◽  
Path Planning ◽  
Control Algorithm ◽  
Moving Objects ◽  
Impedance Control ◽  
Optimization Theory ◽  
Dynamic Interaction ◽  
Unified Approach ◽  
Simplified Analysis ◽  
Unconstrained Motion

This three-part paper presents a unified approach to the control of a manipulator applicable to free motions, kinematically constrained motions, and dynamic interaction between the manipulator and its environment. In Part I the approach was developed from a consideration of the fundamental mechanics of manipulation. Part II presented techniques for implementing a desired manipulator impedance. In Part III a technique for choosing the impedance appropriate to a given application using optimization theory is presented. Based on a simplified analysis it is shown that if the task objective is to tradeoff interface forces and motion errors, the manipulator impedance should be proportional to the environmental admittance. An application of impedance control to unconstrained motion is presented. The superposition properties of nonlinear impedances are used to develop a real-time feedback control algorithm which permits a manipulator to avoid unpredictably moving objects without explicit path planning.

Research on a mobile manipulator for biochemical sampling tasks

2017 ◽  
Vol 44 (4) ◽  
pp. 467-478 ◽  
Author(s):  
Weidong Wang ◽  
Wenrui Gao ◽  
DongMei Wu ◽  
Zhijiang Du
Keyword(s):  
Path Planning ◽  
Motion Planning ◽  
Gaussian Process ◽  
Obstacle Avoidance ◽  
Control Architecture ◽  
Content Type ◽  
Planning Strategy ◽  
Universal Control ◽  
Control Scheme ◽  
Avoidance Strategy

Purpose The paper aims to present a tracked robot comprised of several biochemical sampling instruments and a universal control architecture. In addition, a dynamic motion planning strategy and autonomous modules in sampling tasks are designed and illustrated at length. Design/methodology/approach Several sampling instruments with position tolerance and sealing property are specifically developed, and a robotic operation system (ROS)-based universal control architecture is established. Then, based on the system, two typical problems in sampling tasks, i.e. arm motion planning in unknown environment and autonomous modules, are discussed, implemented and tested. Inspired by the idea of Gaussian process classification (GPC) and Gaussian process (GP) information entropy, three-dimensional (3D) geometric modeling and arm obstacle avoidance strategy are implemented and proven successfully. Moreover, autonomous modules during sampling process are discussed and realized. Findings Smooth implementations of the two experiments justify the validity and extensibility of the robot control scheme. Furthermore, the former experiment proves the efficiency of arm obstacle avoidance strategy, while the later one demonstrates the time reduction and accuracy improvement in sampling tasks as the autonomous actions. Practical implications The proposed control architecture can be applied to more mobile and industrial robots for its feasible and extensible scheme, and the utility function in arm path planning strategy can also be utilized for other information-driven exploration tasks. Originality/value Several specific biochemical sampling instruments are presented in detail, while ROS and Moveit! are integrated into the system scheme, making the robot extensible, achievable and real-time. Based on the control scheme, an information-driven path planning algorithm and automation in sampling tasks are conceived and implemented.

Extended state observer–based output feedback control for spacecraft pose tracking with control input saturation

2021 ◽  
pp. 095441002110177
Author(s):  
Kejie Gong ◽  
Ying Liao ◽  
Yafei Mei
Keyword(s):  
Feedback Control ◽  
Output Feedback ◽  
Finite Time ◽  
Output Feedback Control ◽  
State Observer ◽  
Extended State Observer ◽  
Control Input ◽  
Extended State ◽  
Pose Tracking ◽  
Control Scheme

This article proposed an extended state observer (ESO)–based output feedback control scheme for rigid spacecraft pose tracking without velocity feedback, which accounts for inertial uncertainties, external disturbances, and control input constraints. In this research, the 6-DOF tracking error dynamics is described by the exponential coordinates on SE(3). A novel continuous finite-time ESO is proposed to estimate the velocity information and the compound disturbance, and the estimations are utilized in the control law design. The ESO ensures a finite-time uniform ultimately bounded stability of the observation states, which is proved utilizing the homogeneity method. A non-singular finite-time terminal sliding mode controller based on super-twisting technology is proposed, which would drive spacecraft tracking the desired states. The other two observer-based controllers are also proposed for comparison. The superiorities of the proposed control scheme are demonstrated by theory analyses and numerical simulations.

Space robot motion path planning based on fuzzy control algorithm

2021 ◽  
pp. 1-8
Author(s):  
Baoyu Shi ◽  
Hongtao Wu
Keyword(s):  
Path Planning ◽  
Fuzzy Control ◽  
Obstacle Avoidance ◽  
Control Algorithm ◽  
Space Robot ◽  
Robot Motion ◽  
Robot Path Planning ◽  
Behavior Based ◽  
Fuzzy Control Algorithm ◽  
Robot Path

Path planning technology is one of the core technologies of intelligent space robot. Combining image recognition technology and artificial intelligence learning algorithm for robot path planning in unknown space environment has become one of the hot research issues. The purpose of this paper is to propose a spatial robot path planning method based on improved fuzzy control, aiming at the shortcomings of path planning in the current industrial space robot motion control process, and based on fuzzy control algorithm. This paper proposes a fuzzy obstacle avoidance method with speed feedback based on the original advantages of the fuzzy algorithm, which improves the obstacle avoidance performance of space robot under continuous obstacles. At the same time, we integrated the improved fuzzy obstacle avoidance strategy into the behavior-based control technology, making the avoidance become an independent behavioral unit. Divide the path planning into a series of relatively independent behaviors such as fuzzy obstacle avoidance, cruise, trend target, and deadlock by the behavior-based method. According to the interaction information between the space robot and the environment, each behavior acquires the dominance of the robot through the competition mechanism, making the robot complete the specific behavior at a certain moment, and finally realize the path planning. Furthermore, to improve the overall fault tolerance of the space, robot we introduced an elegant downgrade strategy, so that the robot can successfully complete the established task in the case of control command deterioration or failure of important information, avoiding the overall performance deterioration effectively. Therefore, through the simulation experiment of the virtual environment platform, MobotSim concluded that the improved algorithm has high efficiency, high security, and the planned path is more in line with the actual situation, and the method proposed in this paper can make the space robot successfully reach the target position and optimize the spatial path, it also has good robustness and effectiveness.

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