{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,7]],"date-time":"2026-02-07T12:18:41Z","timestamp":1770466721878,"version":"3.49.0"},"reference-count":29,"publisher":"Emerald","issue":"6","license":[{"start":{"date-parts":[[2024,7,19]],"date-time":"2024-07-19T00:00:00Z","timestamp":1721347200000},"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":[[2024,12,2]]},"abstract":"<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>Fast obstacle avoidance path planning is a challenging task for multijoint robots navigating through cluttered workspaces. This paper aims to address this issue by proposing an improved path-planning method based on the distorted space (DS) method, specifically designed for high-dimensional complex environments.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>The proposed method, termed topology-preserved distorted space (TP-DS) method, mitigates the limitations of the original DS method by preserving space topology through elastic deformation. By applying distinct spring constants, the TP-DS autonomously shrinks obstacles to microscopic areas within the configuration space, maintaining consistent topology. This enhancement extends the application scope of the DS method to handle complex environments effectively.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>Comparative analysis demonstrates that the proposed TP-DS method outperforms traditional methods regarding planning efficiency. Successful obstacle avoidance tasks in the cluttered workspace validate its applicability on a physical 6-DOF manipulator, highlighting its potential for industrial implementations.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>The novel TP-DS method generates a topology-preserved collision-free space by leveraging elastic deformation and shows significant capability and efficiency in planning obstacle-avoidance paths in complex application scenarios.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/ir-02-2024-0049","type":"journal-article","created":{"date-parts":[[2024,7,17]],"date-time":"2024-07-17T01:17:00Z","timestamp":1721179020000},"page":"973-984","source":"Crossref","is-referenced-by-count":1,"title":["Topology-preserved distorted space path planning"],"prefix":"10.1108","volume":"51","author":[{"given":"Yangmin","family":"Xie","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiaoni","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rui","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiyan","family":"Cao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hang","family":"Shi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","published-online":{"date-parts":[[2024,7,19]]},"reference":[{"issue":"6","key":"key2024112907362115100_ref001","doi-asserted-by":"crossref","first-page":"1575","DOI":"10.1007\/s10514-018-9817-3","article-title":"Combined heuristic task and motion planning for bi-manual robots","volume":"43","year":"2019","journal-title":"Autonomous Robots"},{"issue":"5\/8","key":"key2024112907362115100_ref002","first-page":"1401","article-title":"Semi-lazy probabilistic roadmap: a parameter-tuned, resilient and robust path planning method for manipulator robots","volume":"89","year":"2017","journal-title":"The International Journal of Advanced Manufacturing Technology"},{"issue":"2","key":"key2024112907362115100_ref003","doi-asserted-by":"crossref","first-page":"882","DOI":"10.1109\/LRA.2021.3133603","article-title":"Motionbenchmaker: a tool to generate and benchmark motion planning datasets","volume":"7","year":"2022","journal-title":"IEEE Robotics and Automation Letters"},{"issue":"7","key":"key2024112907362115100_ref004","doi-asserted-by":"crossref","first-page":"1585","DOI":"10.1017\/S0263574716000321","article-title":"Path planning in distorted configuration space","volume":"35","year":"2017","journal-title":"Robotica"},{"issue":"2","key":"key2024112907362115100_ref005","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1109\/TASE.2015.2487881","article-title":"Optimal path planning in complex cost spaces with sampling-based algorithms","volume":"13","year":"2016","journal-title":"IEEE Transactions on Automation Science and Engineering"},{"issue":"2","key":"key2024112907362115100_ref006","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1002\/rob.20109","article-title":"Using interpolation to improve path planning: the field D* algorithm","volume":"23","year":"2006","journal-title":"Journal of Field Robotics"},{"key":"key2024112907362115100_ref007","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/j.robot.2018.04.007","article-title":"An improved A* algorithm for the industrial robot path planning with high success rate and short length","volume":"106","year":"2018","journal-title":"Robotics and Autonomous Systems"},{"issue":"5","key":"key2024112907362115100_ref008","doi-asserted-by":"crossref","first-page":"543","DOI":"10.1177\/0278364919890396","article-title":"Batch informed trees (BIT*): informed asymptotically optimal anytime search","volume":"39","year":"2020","journal-title":"The International Journal of Robotics Research"},{"key":"key2024112907362115100_ref009","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1109\/ICRA.2019.8793898","article-title":"Moveit! 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