Abstract
With the development of sensor fusion technologies, there has been a lot of research on intelligent ground vehicles, where obstacle detection is one of the key aspects of vehicle driving. Obstacle detection is a complicated task, which involves the diversity of obstacles, sensor characteristics, and environmental conditions. While the on-road driver assistance system or autonomous driving system has been well researched, the methods developed for the structured road of city scenes may fail in an off-road environment because of its uncertainty and diversity. A single type of sensor finds it hard to satisfy the needs of obstacle detection because of the sensing limitations in range, signal features, and working conditions of detection, and this motivates researchers and engineers to develop multi–sensor fusion and system integration methodology. This survey aims at summarizing the main considerations for the onboard multi-sensor configuration of intelligent ground vehicles in the off-road environments and providing users with a guideline for selecting sensors based on their performance requirements and application environments. State-of-the-art multi-sensor fusion methods and system prototypes are reviewed and associated to the corresponding heterogeneous sensor configurations. Finally, emerging technologies and challenges are discussed for future study.
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Jin-wen HU guided and designed the research. Bo-yin ZHENG and Ce WANG drafted the manuscript. Chun-hui ZHAO and Xiao-lei HOU collected the relevant materials. Quan PAN and Zhao XU helped organize the manuscript. Jin-wen HU revised and finalized the paper.
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Jin-wen HU, Bo-yin ZHENG, Ce WANG, Chun-hui ZHAO, Xiao-lei HOU, Quan PAN, and Zhao XU declare that they have no conflict of interest.
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Project supported by the National Natural Science Foundation of China (Nos. 61603303, 61803309, and 61703343), the Natural Science Foundation of Shaanxi Province, China (No. 2018JQ6070), the China Postdoctoral Science Foundation (No. 2018M633574), and the Fundamental Research Funds for the Central Universities, China (Nos. 3102019ZDHKY02 and 3102018JCC003)
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Hu, Jw., Zheng, By., Wang, C. et al. A survey on multi-sensor fusion based obstacle detection for intelligent ground vehicles in off-road environments. Front Inform Technol Electron Eng 21, 675–692 (2020). https://doi.org/10.1631/FITEE.1900518
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DOI: https://doi.org/10.1631/FITEE.1900518