Hao Lv , Liyuan Liu , Yuming Gao , Shun Zhao, Panpan Yang, Zonggao Mu
{"title":"A compound planning algorithm considering both collision detection and obstacle avoidance for intelligent demolition robots","authors":"Hao Lv , Liyuan Liu , Yuming Gao , Shun Zhao, Panpan Yang, Zonggao Mu","doi":"10.1016/j.robot.2024.104781","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"181 ","pages":"Article 104781"},"PeriodicalIF":4.3000,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Robotics and Autonomous Systems","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0921889024001659","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
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.
期刊介绍:
Robotics and Autonomous Systems will carry articles describing fundamental developments in the field of robotics, with special emphasis on autonomous systems. An important goal of this journal is to extend the state of the art in both symbolic and sensory based robot control and learning in the context of autonomous systems.
Robotics and Autonomous Systems will carry articles on the theoretical, computational and experimental aspects of autonomous systems, or modules of such systems.