The 2nd BARN (Benchmark Autonomous Robot Navigation) Challenge took place at the 2023 IEEE International Conference on Robotics and Automation (ICRA 2023) in London, UK and continued to evaluate the performance of state-of-the-art autonomous ground navigation systems in highly constrained environments. Compared to The 1st BARN Challenge at ICRA 2022 in Philadelphia, the competition has grown significantly in size, doubling the numbers of participants in both the simulation qualifier and physical finals: Ten teams from all over the world participated in the qualifying simulation competition, six of which were invited to compete with each other in three physical obstacle courses at the conference center in London, and three teams won the challenge by navigating a Clearpath Jackal robot from a predefined start to a goal with the shortest amount of time without colliding with any obstacle. The competition results, compared to last year, suggest that the teams are making progress toward more robust and efficient ground navigation systems that work out-of-the-box in many obstacle environments. However, a significant amount of fine-tuning is still needed onsite to cater to different difficult navigation scenarios. Furthermore, challenges still remain for many teams when facing extremely cluttered obstacles and increasing navigation speed. In this article, we discuss the challenge, the approaches used by the three winning teams, and lessons learned to direct future research.

翻译：第二届BARN（基准自主机器人导航）挑战赛于2023年IEEE国际机器人与自动化大会（ICRA 2023）在英国伦敦举行，继续评估了最先进的自主地面导航系统在高度受限环境中的性能。与2022年在费城举行的第一届BARN挑战赛相比，本次竞赛规模显著扩大，模拟资格赛和实体决赛的参赛人数均翻了一番：来自全球的十个团队参加了资格赛模拟竞赛，其中六个团队受邀在伦敦会议中心的三个实体障碍赛道中相互竞技，最终三个团队通过操控Clearpath Jackal机器人，以最短时间从预定义起点抵达终点且未发生任何碰撞，赢得了挑战赛。与去年相比，竞赛结果表明，各团队在开发能够即插即用于多种障碍环境、更鲁棒且高效的地面导航系统方面取得了进展。然而，现场仍需针对不同困难的导航场景进行大量微调。此外，许多团队在面对极端杂乱障碍物和提升导航速度时仍面临挑战。本文讨论了此次挑战赛、三个获胜团队采用的方法，以及为未来研究提供指导的经验教训。