{"title":"改进的时间弹性带碰撞检测算法","authors":"Wanyu Dai, Xianghua Ma","doi":"10.1145/3512576.3512592","DOIUrl":null,"url":null,"abstract":"When TEB (Time Elastic Band) algorithm is applied to the dynamic obstacle avoidance of robots, it has the problem of too much calculation and easy to collide with dynamic obstacles. To solve this problem, an improved robot collision detection method is proposed. Firstly, A* algorithm is used for global path planning, and then TEB algorithm is selected as the core algorithm of the local path planning algorithm. Based on the geometric relationship between the robot and the obstacle, the mathematical model is established, the corresponding collision strategy is designed, the motion parameters of the robot and the obstacle are calculated, the collision risk is determined and whether to use the TEB algorithm to avoid the obstacle is determined. The simulation results show that the path planned by TEB algorithm is smoother than that planned by A* algorithm. And the path length, iteration times and running time after adding collision detection path planning algorithm are greatly shortened, which proves the real-time and effectiveness of the improved algorithm","PeriodicalId":278114,"journal":{"name":"Proceedings of the 2021 9th International Conference on Information Technology: IoT and Smart City","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Improvement of collision detection using Time Elastic Band algorithm\",\"authors\":\"Wanyu Dai, Xianghua Ma\",\"doi\":\"10.1145/3512576.3512592\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"When TEB (Time Elastic Band) algorithm is applied to the dynamic obstacle avoidance of robots, it has the problem of too much calculation and easy to collide with dynamic obstacles. To solve this problem, an improved robot collision detection method is proposed. Firstly, A* algorithm is used for global path planning, and then TEB algorithm is selected as the core algorithm of the local path planning algorithm. Based on the geometric relationship between the robot and the obstacle, the mathematical model is established, the corresponding collision strategy is designed, the motion parameters of the robot and the obstacle are calculated, the collision risk is determined and whether to use the TEB algorithm to avoid the obstacle is determined. The simulation results show that the path planned by TEB algorithm is smoother than that planned by A* algorithm. And the path length, iteration times and running time after adding collision detection path planning algorithm are greatly shortened, which proves the real-time and effectiveness of the improved algorithm\",\"PeriodicalId\":278114,\"journal\":{\"name\":\"Proceedings of the 2021 9th International Conference on Information Technology: IoT and Smart City\",\"volume\":\"67 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2021 9th International Conference on Information Technology: IoT and Smart City\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3512576.3512592\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2021 9th International Conference on Information Technology: IoT and Smart City","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3512576.3512592","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Improvement of collision detection using Time Elastic Band algorithm
When TEB (Time Elastic Band) algorithm is applied to the dynamic obstacle avoidance of robots, it has the problem of too much calculation and easy to collide with dynamic obstacles. To solve this problem, an improved robot collision detection method is proposed. Firstly, A* algorithm is used for global path planning, and then TEB algorithm is selected as the core algorithm of the local path planning algorithm. Based on the geometric relationship between the robot and the obstacle, the mathematical model is established, the corresponding collision strategy is designed, the motion parameters of the robot and the obstacle are calculated, the collision risk is determined and whether to use the TEB algorithm to avoid the obstacle is determined. The simulation results show that the path planned by TEB algorithm is smoother than that planned by A* algorithm. And the path length, iteration times and running time after adding collision detection path planning algorithm are greatly shortened, which proves the real-time and effectiveness of the improved algorithm