Obstacle Avoidance Strategy and Implementation for Unmanned Ground Vehicle Using LIDAR
Regarding safety, obstacle avoidance has been considered as one of the most important features among ADAS systems for ground vehicles. However, the implementation of obstacle avoidance functions to commercial vehicles are still under progress. In this paper, we demonstrate a complete process of obstacle avoidance strategy for unmanned ground vehicle and implement the strategy on the self-developed Arduino based RC Car. In this process, the sensor LIDAR was used to detect the obstacles on the fore-path. Based on the measured LIDAR data, an optimized path is automatically generated with accommodation of current car position, obstacle locations, car operation capability and global environmental restrictions. The path planning is updated in real time while new or changing obstacles being detected. This algorithm is validated by the simulation results with the RC car. The comparison will be discussed at the end of this paper. The successful implementation of the proposed strategy demonstrates the feasibility of this obstacle avoidance methodology, which can be applied to commercial autonomous vehicle.
- Record URL:
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/1946391X
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Supplemental Notes:
- Abstract reprinted with permission of SAE International.
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Authors:
- Wang, Yang
- Goila, Ankit
- Shetty, Rahul
- Heydari, Mahdi
- Desai, Ambarish
- Yang, Hanlong
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Conference:
- WCX™ 17: SAE World Congress Experience
- Location: Detroit Michigan, United States
- Date: 2017-4-4 to 2017-4-6
- Publication Date: 2017-3-28
Language
- English
Media Info
- Media Type: Web
- Features: Figures; Photos; References;
- Pagination: pp 50-55
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Serial:
- SAE International Journal of Commercial Vehicles
- Volume: 10
- Issue Number: 1
- Publisher: SAE International
- ISSN: 1946-391X
- EISSN: 1946-3928
- Serial URL: https://www.sae.org/publications/collections/content/E-JOURNAL-02/
Subject/Index Terms
- TRT Terms: Algorithms; Crash avoidance systems; Driver support systems; Feasibility analysis; Implementation; Intelligent vehicles; Laser radar; Optimization; Simulation; Trajectory control
- Subject Areas: Data and Information Technology; Highways; Motor Carriers; Safety and Human Factors; Vehicles and Equipment;
Filing Info
- Accession Number: 01634760
- Record Type: Publication
- Source Agency: SAE International
- Report/Paper Numbers: 2017-01-0118
- Files: TRIS, SAE
- Created Date: May 16 2017 9:30AM