Occlusion-Aware Path Planning to Promote Infrared Positioning Accuracy for Autonomous Driving in a Warehouse
Infrared positioning is a critical module in an indoor autonomous vehicle platform. In an infrared positioning system, the ego vehicle is equipped with an infrared emitter while the infrared receivers are fixed onto the ceiling. The infrared positioning result is accurate only when the number of val...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-12-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/10/24/3093 |
| _version_ | 1797505221782405120 |
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| author | Bai Li Shiqi Tang Youmin Zhang Xiang Zhong |
| author_facet | Bai Li Shiqi Tang Youmin Zhang Xiang Zhong |
| author_sort | Bai Li |
| collection | DOAJ |
| description | Infrared positioning is a critical module in an indoor autonomous vehicle platform. In an infrared positioning system, the ego vehicle is equipped with an infrared emitter while the infrared receivers are fixed onto the ceiling. The infrared positioning result is accurate only when the number of valid infrared receivers is more than three. An infrared receiver easily becomes invalid if it does not receive light from the infrared emitter due to indoor occlusions. This study proposes an occlusion-aware path planner that enables an autonomous vehicle to navigate toward the occlusion-free part of the drivable area. The planner consists of four layers. In layer one, a homotopic A* path is searched for in the 2D grid map to roughly connect the initial and goal points. In layer two, a curvature-continuous reference line is planned close to the A* path using numerical optimal control. In layer three, a Frenet frame is constructed along the reference line, followed by a search for an occlusion-aware path within that frame via dynamic programming. In layer four, a curvature-continuous path is optimized via quadratic programming within the Frenet frame. A path planned within the Frenet frame may violate the curvature bounds in a real-world Cartesian frame; thus, layer four is implemented through trial and error. Simulation results in CarSim software show that the derived paths reduce the poor positioning risk and are easily tracked by a controller. |
| first_indexed | 2024-03-10T04:15:31Z |
| format | Article |
| id | doaj.art-e940d443d18b4501bbc4f85ce5851c01 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-10T04:15:31Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-e940d443d18b4501bbc4f85ce5851c012023-11-23T08:02:01ZengMDPI AGElectronics2079-92922021-12-011024309310.3390/electronics10243093Occlusion-Aware Path Planning to Promote Infrared Positioning Accuracy for Autonomous Driving in a WarehouseBai Li0Shiqi Tang1Youmin Zhang2Xiang Zhong3College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, ChinaCollege of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, ChinaDepartment of Mechanical, Industrial and Aerospace Engineering, Concordia University, Montreal, QC H3G 1M8, CanadaCollege of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, ChinaInfrared positioning is a critical module in an indoor autonomous vehicle platform. In an infrared positioning system, the ego vehicle is equipped with an infrared emitter while the infrared receivers are fixed onto the ceiling. The infrared positioning result is accurate only when the number of valid infrared receivers is more than three. An infrared receiver easily becomes invalid if it does not receive light from the infrared emitter due to indoor occlusions. This study proposes an occlusion-aware path planner that enables an autonomous vehicle to navigate toward the occlusion-free part of the drivable area. The planner consists of four layers. In layer one, a homotopic A* path is searched for in the 2D grid map to roughly connect the initial and goal points. In layer two, a curvature-continuous reference line is planned close to the A* path using numerical optimal control. In layer three, a Frenet frame is constructed along the reference line, followed by a search for an occlusion-aware path within that frame via dynamic programming. In layer four, a curvature-continuous path is optimized via quadratic programming within the Frenet frame. A path planned within the Frenet frame may violate the curvature bounds in a real-world Cartesian frame; thus, layer four is implemented through trial and error. Simulation results in CarSim software show that the derived paths reduce the poor positioning risk and are easily tracked by a controller.https://www.mdpi.com/2079-9292/10/24/3093autonomous vehicleinfrared positioningocclusion-aware path planningnumerical optimal controldynamic programmingquadratic program |
| spellingShingle | Bai Li Shiqi Tang Youmin Zhang Xiang Zhong Occlusion-Aware Path Planning to Promote Infrared Positioning Accuracy for Autonomous Driving in a Warehouse Electronics autonomous vehicle infrared positioning occlusion-aware path planning numerical optimal control dynamic programming quadratic program |
| title | Occlusion-Aware Path Planning to Promote Infrared Positioning Accuracy for Autonomous Driving in a Warehouse |
| title_full | Occlusion-Aware Path Planning to Promote Infrared Positioning Accuracy for Autonomous Driving in a Warehouse |
| title_fullStr | Occlusion-Aware Path Planning to Promote Infrared Positioning Accuracy for Autonomous Driving in a Warehouse |
| title_full_unstemmed | Occlusion-Aware Path Planning to Promote Infrared Positioning Accuracy for Autonomous Driving in a Warehouse |
| title_short | Occlusion-Aware Path Planning to Promote Infrared Positioning Accuracy for Autonomous Driving in a Warehouse |
| title_sort | occlusion aware path planning to promote infrared positioning accuracy for autonomous driving in a warehouse |
| topic | autonomous vehicle infrared positioning occlusion-aware path planning numerical optimal control dynamic programming quadratic program |
| url | https://www.mdpi.com/2079-9292/10/24/3093 |
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