Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 9, Issue 1


Published
on

June 7, 2024


Pages


DOI

Article

Application of automatic driving task serialisation monitoring for operating robots

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Authors

Yiming Bai Affiliation:
Zhongshan Power Supply Bureau of Guangdong Power Grid Company Limited, Zhongshan, Guangdong, 528401, China.
, Zhijie Ruan Affiliation:
Zhongshan Power Supply Bureau of Guangdong Power Grid Company Limited., Zhongshan, Guangdong, 528401, China.
, Zhenhua Peng Affiliation:
Zhongshan Power Supply Bureau of Guangdong Power Grid Company Limited., Zhongshan, Guangdong, 528401, China.
, Dabing Ruan Affiliation:
Zhongshan Power Supply Bureau of Guangdong Power Grid Company Limited., Zhongshan, Guangdong, 528401, China.
, Shaoming Liang Affiliation:
Zhongshan Power Supply Bureau of Guangdong Power Grid Company Limited., Zhongshan, Guangdong, 528401, China.
, Bingsheng Zhang Affiliation:
Zhongshan Power Supply Bureau of Guangdong Power Grid Company Limited., Zhongshan, Guangdong, 528401, China.
and Xinsheng Liu Affiliation:
Zhongshan Power Supply Bureau of Guangdong Power Grid Company Limited., Zhongshan, Guangdong, 528401, China.


Abstract

With the increasing application of industrial robots, more and more simple and repetitive operations in industrial automated production lines are replaced by industrial robots. In this study, a path planning algorithm is proposed for the autopilot task of an operating robot to find the optimal path from the start point to the goal point under the constraints of safe obstacle avoidance, shortest distance, and fastest time. Forward kinematics is used to detect whether it will collide with environmental obstacles until the first feasible result is detected as the end position for navigation. Serialized monitoring is used to obtain the activity information of each computational node, the hardware state information of the system, and the state of the autopilot task processing. Finally, obstacle avoidance navigation experiments on a mobile operating robot are conducted to verify the effectiveness and feasibility of the obstacle avoidance navigation algorithm. The results show that the maximum error of the autopilot task of the operating robot is 2.91cm, and the average error is 0.13 2cm, which is in line with the trajectory tracking error requirements of the operating machine control method and verifies the validity and practicability of this study.


Keywords

Operating robot, Automatic driving, Path planning, Serialized monitoring, Obstacle avoidance navigation, 97P10


Citation

Bai, Y., Ruan, Z., Peng, Z., Ruan, D., Liang, S., Zhang, B., & Liu, X. (2024). Application of automatic driving task serialisation monitoring for operating robots. Applied Mathematics and Nonlinear Sciences, 9(1). https://doi.org/10.2478/amns-2024-1438

Published by: Engineering Journals

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