Path planning algorithm for mobile robots based on clustering-obstacles and quintic trigonometric Bézier curve
Finding a collision-free feasible path for mobile robots is very important because they are essential in many fields such as healthcare, military, and industry. In this paper, a novel Clustering Obstacles (CO)-based path planning algorithm for mobile robots is presented using a quintic trigonometric...
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| Published in | Annals of mathematics and artificial intelligence Vol. 92; no. 2; pp. 235 - 256 |
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| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
Cham
Springer International Publishing
01.04.2024
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1012-2443 1573-7470 |
| DOI | 10.1007/s10472-023-09893-8 |
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| Abstract | Finding a collision-free feasible path for mobile robots is very important because they are essential in many fields such as healthcare, military, and industry. In this paper, a novel Clustering Obstacles (CO)-based path planning algorithm for mobile robots is presented using a quintic trigonometric Bézier curve and its two shape parameters. The CO-based algorithm forms clusters of geometrically shaped obstacles and finds the cluster centers. Moreover, the proposed waypoint algorithm (WP) finds the waypoints of the predefined skeleton path in addition to the start and destination points in an environment. Based on all these points, the predefined quintic trigonometric Bézier path candidates, taking the skeleton path as their convex hull, are then generated using the shape parameters of this curve. Moreover, the performance of the proposed algorithm is compared with K-Means and agglomerative hierarchical algorithms to obtain the quintic trigonometric Bézier paths desired by the user. The experimental results show that the CO-based path planning algorithm achieves better cluster centers and consequently better collision-free predefined paths. |
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| AbstractList | Finding a collision-free feasible path for mobile robots is very important because they are essential in many fields such as healthcare, military, and industry. In this paper, a novel Clustering Obstacles (CO)-based path planning algorithm for mobile robots is presented using a quintic trigonometric Bézier curve and its two shape parameters. The CO-based algorithm forms clusters of geometrically shaped obstacles and finds the cluster centers. Moreover, the proposed waypoint algorithm (WP) finds the waypoints of the predefined skeleton path in addition to the start and destination points in an environment. Based on all these points, the predefined quintic trigonometric Bézier path candidates, taking the skeleton path as their convex hull, are then generated using the shape parameters of this curve. Moreover, the performance of the proposed algorithm is compared with K-Means and agglomerative hierarchical algorithms to obtain the quintic trigonometric Bézier paths desired by the user. The experimental results show that the CO-based path planning algorithm achieves better cluster centers and consequently better collision-free predefined paths. |
| Author | Bulut, Vahide |
| Author_xml | – sequence: 1 givenname: Vahide orcidid: 0000-0002-0786-8860 surname: Bulut fullname: Bulut, Vahide email: vahide.bulut@ikcu.edu.tr organization: Department of Engineering Sciences, Izmir Katip Celebi University |
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| Cites_doi | 10.1109/34.895974 10.1002/cpe.7830 10.1109/TRO.2017.2723903 10.4018/IJDWM.2019040103 10.1108/aa-11-2015-094 10.1088/1742-6596/1873/1/012074 10.1007/s12555-015-0192-y 10.1016/j.asoc.2020.106960 10.1007/s13042-017-0703-7 10.1177/027836498600500106 10.1080/21642583.2021.1880985 10.1155/2022/7412611 10.1109/34.765656 10.1007/s40314-019-0961-y 10.1007/0-387-25465-x_15 10.1109/TETC.2014.2330519 10.1512/iumj.1964.13.13047 10.17576/jsm-2017-4605-17 10.1109/ICAIBD.2019.8836975 10.1007/s10115-007-0114-2 10.1063/1.5041620 10.1109/URAI.2013.6677324 10.1007/978-3-319-01781-5_10 10.1002/cpe.4636 10.1016/j.aml.2008.03.015 10.1007/978-3-319-66963-2_9 10.1109/icamechs54019.2021.9661551 10.1007/s40430-021-02826-8 10.1109/CSCI.2015.92 10.1016/b978-0-12-820045-2.00006-4 10.1155/2014/623156 10.23919/ACC.2018.8430891 |
| ContentType | Journal Article |
| Copyright | The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| Keywords | Quintic trigonometric Bézier curve Path planning K-Means Agglomerative hierarchical clustering Shape parameters |
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| SubjectTerms | Algorithms Artificial Intelligence Barriers Clustering Collision avoidance Complex Systems Computer Science Convexity Curves Mathematics Parameters Path planning Robots Waypoints |
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| Title | Path planning algorithm for mobile robots based on clustering-obstacles and quintic trigonometric Bézier curve |
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