Omni-Directional Obstacle Extraction based on Occupancy Grid Maps for Autonomous Vehicle

自動車の自律走行のためのOccupancy Grid Maps に基づく全方位障害物検出

Recently, technologies related to autonomous vehicles are researched all over the world. For such autonomous vehicles, it is important to extract small obstacles such as curb stone, and it is also necessary to recognize drivable area in omni-direction not affected by occlusions. In this report, the authors propose obstacle extraction method based on Occupancy Grid Maps to overcome these problems. Moreover, the system overview of the authors' autonomous vehicle will be shown and result of proposed algorithm at a demonstration event in the Tokyo Motor Show 2011 will also be shown.近年自律自動運転自動車に関する研究が世界各国で行われている.このような自律走行車両には縁石等の小さな物体の検知が必要となる.また,オクルージョン脳影響を極力抑え,全方位の走行可能領域を明らかにする必要もある.そこで本研究ではOccupancy Grid Maps に基づきこれらの問題を解決する手法を提案する.また,提案手法を用いて実施した東京モーターショー2011 におけるデモ結果について報告する.


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  • Accession Number: 01676198
  • Record Type: Publication
  • Source Agency: Japan Science and Technology Agency (JST)
  • Files: TRIS, JSTAGE
  • Created Date: Jan 31 2018 3:14PM