A compound planning algorithm considering both collision detection and obstacle avoidance for intelligent demolition robots

•A compound planning algorithm for intelligent demolition robots working without collision in confined nuclear plant.•A collision detection function based on improved dual vector method to detect safe distance between the robot and obstacles.•An obstacle avoidance function based on modified gradient...

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Veröffentlicht in:Robotics and autonomous systems Jg. 181; S. 104781
Hauptverfasser: Lv, Hao, Liu, Liyuan, Gao, Yuming, Zhao, Shun, Yang, Panpan, Mu, Zonggao
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier B.V 01.11.2024
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ISSN:0921-8890
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Zusammenfassung:•A compound planning algorithm for intelligent demolition robots working without collision in confined nuclear plant.•A collision detection function based on improved dual vector method to detect safe distance between the robot and obstacles.•An obstacle avoidance function based on modified gradient projection method considering multi-task transformation. This paper presents a compound planning algorithm considering both collision detection and obstacle avoidance for intelligent demolition robots working safely in high-radiation environments. Firstly, configurations and kinematics of the intelligent demolition robot are detailed to detect the possible obstacles in its workspace. A collision detection function based on the improved dual vector method is proposed to detect the different distances between the robot and obstacles in three cases: a point and a line segment, two line segments, and a line segment and a geometric shape. This function can also be applied to detect collisions with various obstacles of different shapes reasonably and efficiently. Furthermore, an obstacle avoidance function based on modified gradient projection method considering multi-task transformation is proposed. According to the different distances between the robot and the obstacle, it can be used in three situations: end obstacle avoidance task, end effector operation task, and end trajectory tracking task. This function can be applied to avoid obstacles both in the workspace and on the desired path. Finally, a simulation system is established to verify the collision detection and obstacle avoidance algorithms of the intelligent demolition robot. An experiment was conducted on the intelligent demolition robot. This robot can successfully achieve the expected trajectory with the method described in this article. Results of simulation and experiment demonstrate that obstacles both in workspace and on desired path can be detected and avoided properly.
ISSN:0921-8890
DOI:10.1016/j.robot.2024.104781