<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>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.</p>
</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.

Application of automatic driving task serialisation monitoring for operating robots

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

With the increasing application of industrial robots, more and more simple and repetitive operations in industrial automated production lines are replaced by...

Application of automatic driving task serialisation monitoring for operating robots

Published Online: Jun 07, 2024

Page range: -

Received: Feb 19, 2024

Accepted: May 03, 2024

DOI: https://doi.org/10.2478/amns-2024-1438

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

© 2024 Yiming Bai et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Application of automatic driving task serialisation monitoring for operating robots

Published Online: Jun 07, 2024

Page range: -

Received: Feb 19, 2024

Accepted: May 03, 2024

DOI: https://doi.org/10.2478/amns-2024-1438

KeywordsOperating robot, Automatic driving, Path planning, Serialized monitoring, Obstacle avoidance navigation

© 2024 Yiming Bai et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

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