{"title":"三维路径规划与避障算法在超障机器人中的应用","authors":"Y. Huang, Huang Shi, Wang Hao, Ruifeng Meng","doi":"10.1109/ECBIOS57802.2023.10218652","DOIUrl":null,"url":null,"abstract":"This article presents a MMP algorithm that combines a 3-D path planning algorithm with a DWA obstacle avoidance algorithm, to enable obstacle-overcoming robots to navigate complex, unstructured scenes. To achieve this, a novel A-star algorithm is proposed that can switch to a greedy best-first strategy algorithm based on the characteristics of the scene. The path planning algorithm is integrated with the DWA algorithm, allowing for local dynamic obstacle avoidance while following the global planned path. Additionally, the algorithm enables the robot to correct its path after obstacle avoidance and overcoming. The feasibility and robustness of the algorithms are demonstrated through simulation experiments in a factory with several complex environments. The algorithms quickly generate a reasonable 3-D path and perform reliable local obstacle avoidance, while taking into account the characteristics of the scene and motion obstacles.","PeriodicalId":334600,"journal":{"name":"2023 IEEE 5th Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Application of 3-D Path Planning and Obstacle Avoidance Algorithms on Obstacle-Overcoming Robots\",\"authors\":\"Y. Huang, Huang Shi, Wang Hao, Ruifeng Meng\",\"doi\":\"10.1109/ECBIOS57802.2023.10218652\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article presents a MMP algorithm that combines a 3-D path planning algorithm with a DWA obstacle avoidance algorithm, to enable obstacle-overcoming robots to navigate complex, unstructured scenes. To achieve this, a novel A-star algorithm is proposed that can switch to a greedy best-first strategy algorithm based on the characteristics of the scene. The path planning algorithm is integrated with the DWA algorithm, allowing for local dynamic obstacle avoidance while following the global planned path. Additionally, the algorithm enables the robot to correct its path after obstacle avoidance and overcoming. The feasibility and robustness of the algorithms are demonstrated through simulation experiments in a factory with several complex environments. The algorithms quickly generate a reasonable 3-D path and perform reliable local obstacle avoidance, while taking into account the characteristics of the scene and motion obstacles.\",\"PeriodicalId\":334600,\"journal\":{\"name\":\"2023 IEEE 5th Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS)\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE 5th Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ECBIOS57802.2023.10218652\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE 5th Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECBIOS57802.2023.10218652","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application of 3-D Path Planning and Obstacle Avoidance Algorithms on Obstacle-Overcoming Robots
This article presents a MMP algorithm that combines a 3-D path planning algorithm with a DWA obstacle avoidance algorithm, to enable obstacle-overcoming robots to navigate complex, unstructured scenes. To achieve this, a novel A-star algorithm is proposed that can switch to a greedy best-first strategy algorithm based on the characteristics of the scene. The path planning algorithm is integrated with the DWA algorithm, allowing for local dynamic obstacle avoidance while following the global planned path. Additionally, the algorithm enables the robot to correct its path after obstacle avoidance and overcoming. The feasibility and robustness of the algorithms are demonstrated through simulation experiments in a factory with several complex environments. The algorithms quickly generate a reasonable 3-D path and perform reliable local obstacle avoidance, while taking into account the characteristics of the scene and motion obstacles.