{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T00:45:17Z","timestamp":1778201117404,"version":"3.51.4"},"reference-count":18,"publisher":"Emerald","issue":"2","license":[{"start":{"date-parts":[[2021,10,14]],"date-time":"2021-10-14T00:00:00Z","timestamp":1634169600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IR"],"published-print":{"date-parts":[[2022,2,11]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title><jats:p>This paper aims to resolve issues of the traditional artificial potential field method, such as falling into local minima, low success rate and lack of ability to sense the obstacle shapes in the planning process.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title><jats:p>In this paper, an improved artificial potential field method is proposed, where the object can leave the local minima point, where the algorithm falls into, while it avoids the obstacle, following a shorter feasible path along the repulsive equipotential surface, which is locally optimized. The whole obstacle avoidance process is based on the improved artificial potential field method, applied during the mechanical arm path planning action, along the motion from the starting point to the target point.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>Simulation results show that the algorithm in this paper can effectively perceive the obstacle shape in all the selected cases and can effectively shorten the distance of the planned path by 13%\u201341% with significantly higher planning efficiency compared with the improved artificial potential field method based on rapidly-exploring random tree. The experimental results show that the improved artificial potential field method can effectively plan a smooth collision-free path for the object, based on an algorithm with good environmental adaptability.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>An improved artificial potential field method is proposed for optimized obstacle avoidance path planning of a mechanical arm in three-dimensional space. This new approach aims to resolve issues of the traditional artificial potential field method, such as falling into local minima, low success rate and lack of ability to sense the obstacle shapes in the planning process.<\/jats:p><\/jats:sec>","DOI":"10.1108\/ir-06-2021-0120","type":"journal-article","created":{"date-parts":[[2021,10,12]],"date-time":"2021-10-12T20:29:57Z","timestamp":1634070597000},"page":"271-279","source":"Crossref","is-referenced-by-count":52,"title":["Mechanical arm obstacle avoidance path planning based on improved artificial potential field method"],"prefix":"10.1108","volume":"49","author":[{"given":"Tianying","family":"Xu","sequence":"first","affiliation":[]},{"given":"Haibo","family":"Zhou","sequence":"additional","affiliation":[]},{"given":"Shuaixia","family":"Tan","sequence":"additional","affiliation":[]},{"given":"Zhiqiang","family":"Li","sequence":"additional","affiliation":[]},{"given":"Xia","family":"Ju","sequence":"additional","affiliation":[]},{"given":"Yichang","family":"Peng","sequence":"additional","affiliation":[]}],"member":"140","published-online":{"date-parts":[[2021,10,14]]},"reference":[{"issue":"2","key":"key2022102108063461700_ref001","doi-asserted-by":"crossref","first-page":"1235","DOI":"10.1016\/j.aej.2016.03.042","article-title":"Dual-well potential field function for articulated manipulator trajectory planning","volume":"55","author":"Badawy and Ahmed","year":"2016","journal-title":"Alexandria Engineering Journal"},{"key":"key2022102108063461700_ref002","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/j.robot.2016.12.008","article-title":"Optimal path planning and execution for mobile robots using genetic algorithm and adaptive fuzzy-logic control","volume":"89","year":"2017","journal-title":"Robotics and Autonomous Systems"},{"issue":"1","key":"key2022102108063461700_ref003","first-page":"217","article-title":"Path planning and collision avoidance for a Multi-Arm space maneuverable robot","volume":"54","year":"2017","journal-title":"IEEE Transactions on Aerospace and Electronic Systems"},{"key":"key2022102108063461700_ref004","article-title":"6-DOF robotic obstacle avoidance path planning based on artificial potential field method","volume-title":"2019 16th International Conference on Ubiquitous Robots (UR)","year":"2019"},{"issue":"3","key":"key2022102108063461700_ref005","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1108\/IR-01-2018-0017","article-title":"Advances in robotics for additive\/hybrid manufacturing: robot control, speech interface and path planning (#literatiawards winner 2019)","volume":"45","year":"2018","journal-title":"Industrial Robot"},{"issue":"1","key":"key2022102108063461700_ref006","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1007\/s40032-014-0099-z","article-title":"Obstacle avoidance path planning of space manipulator based on improved artificial potential field method","volume":"95","year":"2014","journal-title":"Journal of the Institution of Engineers (India): Series C"},{"key":"key2022102108063461700_ref007","doi-asserted-by":"crossref","first-page":"3563846","DOI":"10.1155\/2018\/3563846","article-title":"Collision-Free Path-Planning for Six-DOF serial harvesting robot based on energy optimal and artificial potential field","volume":"2018","year":"2018","journal-title":"Complexity"},{"issue":"4","key":"key2022102108063461700_ref008","doi-asserted-by":"crossref","first-page":"535","DOI":"10.1109\/TSMC.2017.2697447","article-title":"Output-Feedback Path-Following control of autonomous underwater vehicles based on an extended state observer and projection neural networks","volume":"48","year":"2018","journal-title":"IEEE Transactions on Systems, Man, and Cybernetics: Systems"},{"issue":"6","key":"key2022102108063461700_ref009","doi-asserted-by":"crossref","first-page":"657","DOI":"10.1108\/IR-01-2016-0006","article-title":"Multiple manipulators path planning using double a*","volume":"43","year":"2016","journal-title":"Industrial Robot: An International Journal"},{"key":"key2022102108063461700_ref010","article-title":"Obstacle avoidance path planning for manipulator based on variable-step artificial potential method","volume-title":"Control & Decision Conference","year":"2015"},{"issue":"5","key":"key2022102108063461700_ref011","first-page":"203","article-title":"An improved artificial potential field method of trajectory planning and obstacle avoidance for redundant manipulators","volume":"15","year":"2018","journal-title":"International Journal of Advanced Robotic Systems"},{"key":"key2022102108063461700_ref012","article-title":"Improved cubic B-spline curve method for path optimization of manipulator obstacle avoidance","year":"2019"},{"key":"key2022102108063461700_ref013","doi-asserted-by":"crossref","first-page":"135513","DOI":"10.1109\/ACCESS.2020.3011211","article-title":"Path planning method with improved artificial potential field \u2013 a reinforcement learning perspective","volume":"8","year":"2020","journal-title":"IEEE Access"},{"key":"key2022102108063461700_ref014","doi-asserted-by":"crossref","first-page":"900","DOI":"10.1109\/ACCESS.2019.2958876","article-title":"A heuristic Rapidly-Exploring random trees method for manipulator motion planning","volume":"8","year":"2020","journal-title":"IEEE Access"},{"issue":"1","key":"key2022102108063461700_ref015","doi-asserted-by":"crossref","first-page":"509","DOI":"10.1186\/s40064-016-2157-x","article-title":"Obstacle avoidance planning of space manipulator end-effector based on improved ant colony algorithm","volume":"5","year":"2016","journal-title":"SpringerPlus"},{"issue":"1","key":"key2022102108063461700_ref016","first-page":"1","article-title":"Virtual target point-based obstacle-avoidance method for manipulator systems in a cluttered environment","volume":"52","year":"2019","journal-title":"Engineering Optimization"},{"key":"key2022102108063461700_ref017","first-page":"1","article-title":"Improved manipulator obstacle avoidance path planning based on potential field method","volume":"2020","year":"2020","journal-title":"Journal of Robotics"},{"issue":"3","key":"key2022102108063461700_ref018","doi-asserted-by":"crossref","first-page":"935","DOI":"10.3390\/app10030935","article-title":"Trajectory optimization of pickup manipulator in obstacle environment based on improved artificial potential field method","volume":"10","year":"2020","journal-title":"Applied Sciences"}],"container-title":["Industrial Robot: the international journal of robotics research and application"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/IR-06-2021-0120\/full\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/IR-06-2021-0120\/full\/html","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T21:39:22Z","timestamp":1753393162000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.emerald.com\/ir\/article\/49\/2\/271-279\/186230"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10,14]]},"references-count":18,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2021,10,14]]},"published-print":{"date-parts":[[2022,2,11]]}},"alternative-id":["10.1108\/IR-06-2021-0120"],"URL":"https:\/\/doi.org\/10.1108\/ir-06-2021-0120","relation":{},"ISSN":["0143-991X","0143-991X"],"issn-type":[{"value":"0143-991X","type":"print"},{"value":"0143-991X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,10,14]]}}}