The RoboSense Challenge: Sense Anything, Navigate Anywhere, Adapt Across Platforms
Abstract
Autonomous systems are increasingly deployed in open and dynamic environments -- from city streets to aerial and indoor spaces -- where perception models must remain reliable under sensor noise, environmental variation, and platform shifts. However, even state-of-the-art methods often degrade under unseen conditions, highlighting the need for robust and generalizable robot sensing. The RoboSense 2025 Challenge is designed to advance robustness and adaptability in robot perception across diverse sensing scenarios. It unifies five complementary research tracks spanning language-grounded decision making, socially compliant navigation, sensor configuration generalization, cross-view and cross-modal correspondence, and cross-platform 3D perception. Together, these tasks form a comprehensive benchmark for evaluating real-world sensing reliability under domain shifts, sensor failures, and platform discrepancies. RoboSense 2025 provides standardized datasets, baseline models, and unified evaluation protocols, enabling large-scale and reproducible comparison of robust perception methods. The challenge attracted 143 teams from 85 institutions across 16 countries, reflecting broad community engagement. By consolidating insights from 23 winning solutions, this report highlights emerging methodological trends, shared design principles, and open challenges across all tracks, marking a step toward building robots that can sense reliably, act robustly, and adapt across platforms in real-world environments.
Keywords
Cite
@article{arxiv.2601.05014,
title = {The RoboSense Challenge: Sense Anything, Navigate Anywhere, Adapt Across Platforms},
author = {Lingdong Kong and Shaoyuan Xie and Zeying Gong and Ye Li and Meng Chu and Ao Liang and Yuhao Dong and Tianshuai Hu and Ronghe Qiu and Rong Li and Hanjiang Hu and Dongyue Lu and Wei Yin and Wenhao Ding and Linfeng Li and Hang Song and Wenwei Zhang and Yuexin Ma and Junwei Liang and Zhedong Zheng and Lai Xing Ng and Benoit R. Cottereau and Wei Tsang Ooi and Ziwei Liu and Zhanpeng Zhang and Weichao Qiu and Wei Zhang and Ji Ao and Jiangpeng Zheng and Siyu Wang and Guang Yang and Zihao Zhang and Yu Zhong and Enzhu Gao and Xinhan Zheng and Xueting Wang and Shouming Li and Yunkai Gao and Siming Lan and Mingfei Han and Xing Hu and Dusan Malic and Christian Fruhwirth-Reisinger and Alexander Prutsch and Wei Lin and Samuel Schulter and Horst Possegger and Linfeng Li and Jian Zhao and Zepeng Yang and Yuhang Song and Bojun Lin and Tianle Zhang and Yuchen Yuan and Chi Zhang and Xuelong Li and Youngseok Kim and Sihwan Hwang and Hyeonjun Jeong and Aodi Wu and Xubo Luo and Erjia Xiao and Lingfeng Zhang and Yingbo Tang and Hao Cheng and Renjing Xu and Wenbo Ding and Lei Zhou and Long Chen and Hangjun Ye and Xiaoshuai Hao and Shuangzhi Li and Junlong Shen and Xingyu Li and Hao Ruan and Jinliang Lin and Zhiming Luo and Yu Zang and Cheng Wang and Hanshi Wang and Xijie Gong and Yixiang Yang and Qianli Ma and Zhipeng Zhang and Wenxiang Shi and Jingmeng Zhou and Weijun Zeng and Kexin Xu and Yuchen Zhang and Haoxiang Fu and Ruibin Hu and Yanbiao Ma and Xiyan Feng and Wenbo Zhang and Lu Zhang and Yunzhi Zhuge and Huchuan Lu and You He and Seungjun Yu and Junsung Park and Youngsun Lim and Hyunjung Shim and Faduo Liang and Zihang Wang and Yiming Peng and Guanyu Zong and Xu Li and Binghao Wang and Hao Wei and Yongxin Ma and Yunke Shi and Shuaipeng Liu and Dong Kong and Yongchun Lin and Huitong Yang and Liang Lei and Haoang Li and Xinliang Zhang and Zhiyong Wang and Xiaofeng Wang and Yuxia Fu and Yadan Luo and Djamahl Etchegaray and Yang Li and Congfei Li and Yuxiang Sun and Wenkai Zhu and Wang Xu and Linru Li and Longjie Liao and Jun Yan and Benwu Wang and Xueliang Ren and Xiaoyu Yue and Jixian Zheng and Jinfeng Wu and Shurui Qin and Wei Cong and Yao He},
journal= {arXiv preprint arXiv:2601.05014},
year = {2026}
}
Comments
Official IROS 2025 RoboSense Challenge Report; 51 pages, 37 figures, 5 tables; Competition Website at https://robosense2025.github.io/