Control and benchmarking of a 7-DOF robotic arm using Gazebo and ROS

Bowei Zhang; Pengcheng Liu

doi:10.7717/peerj-cs.383

Control and benchmarking of a 7-DOF robotic arm using Gazebo and ROS

Bowei Zhang, Pengcheng Liu

Computer Science

Research output: Contribution to journal › Article › peer-review

Abstract

Robot controller plays an important role in controlling the robot. The controller mainly aims to eliminate or suppress the influence of uncertain factors on the control robot. Furthermore, there are many types of controllers, and different types of controllers have different features. To explore the differences between controllers of the same category, this paper studies some controllers from basic controllers and advanced controllers. This paper conducts the benchmarking of the selected controller through pre-set tests. The test task is the most commonly used pick and place. Furthermore, to complete the robustness test, a task of external force interference is also set to observe whether the controller can control the robot arm to return to a normal state. Subsequently, the accuracy, control efficiency, jitter and robustness of the robot arm controlled by the controller are analyzed by comparing the Position and Effort data. Finally, some future works of the benchmarking and reasonable improvement methods are discussed.

Original language	English
Article number	e383
Journal	PeerJ Computer Science
Volume	7
Early online date	23 Mar 2021
DOIs	https://doi.org/10.7717/peerj-cs.383
Publication status	E-pub ahead of print - 23 Mar 2021

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10.7717/peerj-cs.383Licence: CC BY

peerj-cs-383
© 2021, The Author(s)
Final published version, 14 MBLicence: CC BY

Cite this

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abstract = "Robot controller plays an important role in controlling the robot. The controller mainly aims to eliminate or suppress the influence of uncertain factors on the control robot. Furthermore, there are many types of controllers, and different types of controllers have different features. To explore the differences between controllers of the same category, this paper studies some controllers from basic controllers and advanced controllers. This paper conducts the benchmarking of the selected controller through pre-set tests. The test task is the most commonly used pick and place. Furthermore, to complete the robustness test, a task of external force interference is also set to observe whether the controller can control the robot arm to return to a normal state. Subsequently, the accuracy, control efficiency, jitter and robustness of the robot arm controlled by the controller are analyzed by comparing the Position and Effort data. Finally, some future works of the benchmarking and reasonable improvement methods are discussed.",

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