Autonomous navigation of quadrupeds using coverage path planning with morphological skeleton maps
This article proposes a novel method of coverage path planning for the purpose of scanning an unstructured environment autonomously. The method uses the morphological skeleton of a prior 2D navigation map via SLAM to generate a sequence of points of interest (POIs). This sequence is then ordered to...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-07-01
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| Series: | Frontiers in Robotics and AI |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/frobt.2025.1601862/full |
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| author | Alexander James Becoy Alexander James Becoy Kseniia Khomenko Luka Peternel Raj Thilak Rajan |
| author_facet | Alexander James Becoy Alexander James Becoy Kseniia Khomenko Luka Peternel Raj Thilak Rajan |
| author_sort | Alexander James Becoy |
| collection | DOAJ |
| description | This article proposes a novel method of coverage path planning for the purpose of scanning an unstructured environment autonomously. The method uses the morphological skeleton of a prior 2D navigation map via SLAM to generate a sequence of points of interest (POIs). This sequence is then ordered to create an optimal path based on the robot’s current position. To control the high-level operation, a finite state machine (FSM) is used to switch between two modes: navigating toward a POI using Nav2 and scanning the local surroundings. We validate the method in a leveled, indoor, obstacle-free, non-convex environment, evaluating time efficiency and reachability over five trials. The map reader and path planner can quickly process maps of widths and heights ranging between [196,225] pixels and [185,231] pixels in 2.52 ms and 1.7 ms, respectively. Their computation time increases with 22.0 ns/pixel and 8.17 μs/pixel, respectively. The robot managed to reach 86.5% of all waypoints across the five runs. The proposed method suffers from drift occurring in the 2D navigation map. |
| format | Article |
| id | doaj-art-a68ac2e54f39498bbbeba0439575934e |
| institution | DOAJ |
| issn | 2296-9144 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Robotics and AI |
| spelling | doaj-art-a68ac2e54f39498bbbeba0439575934e2025-08-20T02:46:35ZengFrontiers Media S.A.Frontiers in Robotics and AI2296-91442025-07-011210.3389/frobt.2025.16018621601862Autonomous navigation of quadrupeds using coverage path planning with morphological skeleton mapsAlexander James Becoy0Alexander James Becoy1Kseniia Khomenko2Luka Peternel3Raj Thilak Rajan4Department of Cognitive Robotics, Faculty of Mechanical Engineering, Delft University of Technology, Delft, NetherlandsDepartment of Microelectronics, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, NetherlandsDepartment of Cognitive Robotics, Faculty of Mechanical Engineering, Delft University of Technology, Delft, NetherlandsDepartment of Cognitive Robotics, Faculty of Mechanical Engineering, Delft University of Technology, Delft, NetherlandsDepartment of Microelectronics, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, NetherlandsThis article proposes a novel method of coverage path planning for the purpose of scanning an unstructured environment autonomously. The method uses the morphological skeleton of a prior 2D navigation map via SLAM to generate a sequence of points of interest (POIs). This sequence is then ordered to create an optimal path based on the robot’s current position. To control the high-level operation, a finite state machine (FSM) is used to switch between two modes: navigating toward a POI using Nav2 and scanning the local surroundings. We validate the method in a leveled, indoor, obstacle-free, non-convex environment, evaluating time efficiency and reachability over five trials. The map reader and path planner can quickly process maps of widths and heights ranging between [196,225] pixels and [185,231] pixels in 2.52 ms and 1.7 ms, respectively. Their computation time increases with 22.0 ns/pixel and 8.17 μs/pixel, respectively. The robot managed to reach 86.5% of all waypoints across the five runs. The proposed method suffers from drift occurring in the 2D navigation map.https://www.frontiersin.org/articles/10.3389/frobt.2025.1601862/fullquadrupedautonomous navigationunstructured environmentcoverage path planningrobot operating system 2 |
| spellingShingle | Alexander James Becoy Alexander James Becoy Kseniia Khomenko Luka Peternel Raj Thilak Rajan Autonomous navigation of quadrupeds using coverage path planning with morphological skeleton maps Frontiers in Robotics and AI quadruped autonomous navigation unstructured environment coverage path planning robot operating system 2 |
| title | Autonomous navigation of quadrupeds using coverage path planning with morphological skeleton maps |
| title_full | Autonomous navigation of quadrupeds using coverage path planning with morphological skeleton maps |
| title_fullStr | Autonomous navigation of quadrupeds using coverage path planning with morphological skeleton maps |
| title_full_unstemmed | Autonomous navigation of quadrupeds using coverage path planning with morphological skeleton maps |
| title_short | Autonomous navigation of quadrupeds using coverage path planning with morphological skeleton maps |
| title_sort | autonomous navigation of quadrupeds using coverage path planning with morphological skeleton maps |
| topic | quadruped autonomous navigation unstructured environment coverage path planning robot operating system 2 |
| url | https://www.frontiersin.org/articles/10.3389/frobt.2025.1601862/full |
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