activity
20232026
most citedOccLLaMA: An Occupancy-Language-Action Generative World Model for Autonomous Driving

2 citations · 6 across the 9 of their papers we have counts for

collaborators

13 papers

cs.RO2026

AutoSpeed: Annotation-Free Stage-Adaptive Motion Speed Learning for Robot Manipulation

Qingda Hu, Ziheng Qiu, Jieru Zhao +2

Different stages of manipulation tasks exhibit varying levels of difficulty, suggesting stage-dependent motion speeds and temporal prediction horizons. However, existing IL-based v…

cs.RO2026

Learning A Unified Risk Map for Autonomous Driving in Partially Observable Environments

Jie Jia, Yaofeng Su, Zeyu Bao +4

Occlusion-aware prediction remains a critical challenge in autonomous driving due to the inherent uncertainty of unobserved regions. Existing approaches either overestimate risk ba…

cs.RO2026

Unveiling the Surprising Efficacy of Navigation Understanding in End-to-End Autonomous Driving

Zhihua Hua, Junli Wang, Pengfei LI +6

Global navigation information and local scene understanding are two crucial components of autonomous driving systems. However, our experimental results indicate that many end-to-en…

cs.RO2026

CMoE: Contrastive Mixture of Experts for Motion Control and Terrain Adaptation of Humanoid Robots

Shihao Ma, Hongjin Chen, Zijun Xu +6

For effective deployment in real-world environments, humanoid robots must autonomously navigate a diverse range of complex terrains with abrupt transitions. While the Vanilla mixtu…

cs.RO2025

Resolving State Ambiguity in Robot Manipulation via Adaptive Working Memory Recoding

Qingda Hu, Ziheng Qiu, Zijun Xu +7

State ambiguity is common in robotic manipulation. Identical observations may correspond to multiple valid behavior trajectories. The visuomotor policy must correctly extract the a…

cs.RO2025

Drive in Corridors: Enhancing the Safety of End-to-end Autonomous Driving via Corridor Learning and Planning

Zhiwei Zhang, Ruichen Yang, Ke Wu +5

Safety remains one of the most critical challenges in autonomous driving systems. In recent years, the end-to-end driving has shown great promise in advancing vehicle autonomy in a…