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Author:

Zuo, Guoyu (Zuo, Guoyu.) (Scholars:左国玉) | Qiu, Yongkang (Qiu, Yongkang.) | Liu, Yuelei (Liu, Yuelei.) | Huang, Xiangsheng (Huang, Xiangsheng.)

Indexed by:

CPCI-S

Abstract:

In order to improve the safety performance of the robot, this paper proposes an external force detection method for humanoid robot arm without using joint torque sensors, which can detect the external force of the joint space in real time during the operation of the robot. First, Analyses on the structure of the humanoid robot arm is performed, and the model of robot external force detection is established based on robot dynamics and motor dynamics. Then, the error of detection model is analyzed, and the robot dynamic model error is compensated by using the BP network, in order to obtain more accurate external force detection value of the robot. Experiments show that the method can effectively improve the detection accuracy, and the obtained external force detection data can be applied not only to the collision detection in the static state of the robot, but also to the online collision detection when the robot is running, which can ensure the safe operation of the robot.

Keyword:

Author Community:

  • [ 1 ] [Zuo, Guoyu]Beijing Univ Technol, Intelligent Robot Lab, Beijing 100124, Peoples R China
  • [ 2 ] [Qiu, Yongkang]Beijing Univ Technol, Intelligent Robot Lab, Beijing 100124, Peoples R China
  • [ 3 ] [Liu, Yuelei]Beijing Univ Technol, Intelligent Robot Lab, Beijing 100124, Peoples R China
  • [ 4 ] [Huang, Xiangsheng]Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China

Reprint Author's Address:

  • 左国玉

    [Zuo, Guoyu]Beijing Univ Technol, Intelligent Robot Lab, Beijing 100124, Peoples R China

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Source :

2019 9TH IEEE ANNUAL INTERNATIONAL CONFERENCE ON CYBER TECHNOLOGY IN AUTOMATION, CONTROL, AND INTELLIGENT SYSTEMS (IEEE-CYBER 2019)

ISSN: 2379-7711

Year: 2019

Page: 265-270

Language: English

Cited Count:

WoS CC Cited Count: 2

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 4

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