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Author:

Zhang, Enhui (Zhang, Enhui.) | Yu, Jianjun (Yu, Jianjun.) | Li, Meng (Li, Meng.)

Indexed by:

EI Scopus

Abstract:

Using the traditional environmental model and the known control algorithm can lead to the failure of the task easily when teleoperation robot works in unstructured unknown environment, because of the lack of information about the environment around the robot arm and the lack of feedback. To solve this significant problem, a new improved algorithm based on the traditional approximate obstacle avoidance algorithm is proposed in this paper. By adding control algorithm factors, this algorithm will complete the obstacle avoidance in unknown environment through transforming information which is obtained from the obstacle distance detector into each joint and the velocity parameter of the end effector and mapping to the joint movement by Jacobian matrix. Thus, the performance of the robot arm is improved. In addition, the algorithm has the advantages of small computation and fast escape speed. Finally, the simulation experiment of obstacle avoidance is carried out in MATLAB software to verify the effectiveness of the algorithm. The results show that the algorithm can accomplish the obstacle avoidance of teleoperation manipulator in real-time and effectively in unstructured unknown environment. © 2017 IEEE.

Keyword:

Robotic arms MATLAB Biomimetics Remote control Robotics Jacobian matrices Manipulators Collision avoidance Agricultural robots

Author Community:

  • [ 1 ] [Zhang, Enhui]Department of information science, College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China
  • [ 2 ] [Yu, Jianjun]Department of information science, College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China
  • [ 3 ] [Li, Meng]Department of information science, College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China

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Year: 2017

Volume: 2018-January

Page: 1-6

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 2

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 8

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