The RoboSense Challenge: Sense Anything, Navigate Anywhere, Adapt Across Platforms
Lingdong Kong, Shaoyuan Xie, Zeying Gong, Ye Li, Meng Chu, Ao Liang, Yuhao Dong, Tianshuai Hu, Ronghe Qiu, Rong Li, Hanjiang Hu, Dongyue Lu, Wei Yin, Wenhao Ding, Linfeng Li, Hang Song, Wenwei Zhang, Yuexin Ma, Junwei Liang, Zhedong Zheng, Lai Xing Ng, Benoit R. Cottereau

TL;DR
The RoboSense 2025 Challenge aims to advance robust and adaptable perception in autonomous systems across diverse environments by providing standardized benchmarks, datasets, and evaluation protocols, fostering broad community engagement and innovation.
Contribution
This paper introduces the RoboSense 2025 Challenge, a comprehensive benchmark with multiple research tracks, datasets, and evaluation methods to improve perception robustness and adaptability in robotics.
Findings
143 teams participated from 85 institutions
23 winning solutions reveal emerging trends and shared principles
Benchmark highlights open challenges in robust robot sensing
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…
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Taxonomy
TopicsMultimodal Machine Learning Applications · Robotics and Sensor-Based Localization · Social Robot Interaction and HRI
