狭所における自律地上ナビゲーション：ICRA 2024第3回BARNチャレンジからの教訓
Autonomous Ground Navigation in Highly Constrained Spaces: Lessons learned from The 3rd BARN Challenge at ICRA 2024
ICRA 2024で開催された第3回BARNチャレンジを通じて、狭く制約の厳しい環境での自律地上ナビゲーション技術の現状を評価し、上位チームの手法と今後の課題を分析した。
著者: Xuesu Xiao, Zifan Xu, Aniket Datar, Garrett Warnell, Peter Stone, Joshua Julian Damanik, Jaewon Jung, Chala Adane Deresa, Than Duc Huy, Chen Jinyu, Chen Yichen, Joshua Adrian Cahyono, Jingda Wu, Longfei Mo, Mingyang Lv, Bowen Lan, Qingyang Meng, Weizhi Tao, Li Cheng
分類: cs.RO
原文アブストラクト
The 3rd BARN (Benchmark Autonomous Robot Navigation) Challenge took place at the 2024 IEEE International Conference on Robotics and Automation (ICRA 2024) in Yokohama, Japan and continued to evaluate the performance of state-of-the-art autonomous ground navigation systems in highly constrained environments. Similar to the trend in The 1st and 2nd BARN Challenge at ICRA 2022 and 2023 in Philadelphia (North America) and London (Europe), The 3rd BARN Challenge in Yokohama (Asia) became more regional, i.e., mostly Asian teams participated. The size of the competition has slightly shrunk (six simulation teams, four of which were invited to the physical competition). The competition results, compared to last two years, suggest that the field has adopted new machine learning approaches while at the same time slightly converged to a few common practices. However, the regional nature of the physical participants suggests a challenge to promote wider participation all over the world and provide more resources to travel to the venue. In this article, we discuss the challenge, the approaches used by the three winning teams, and lessons learned to direct future research and competitions.
