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cs.RO2026

Learning Whole-Body Humanoid Locomotion via Motion Generation and Motion Tracking

Zewei Zhang, Kehan Wen, Michael Xu +7

Whole-body humanoid locomotion is challenging due to high-dimensional control, morphological instability, and the need for real-time adaptation to various terrains using onboard pe…

cs.RO2026

Learning Locomotion on Discrete Terrain via Minimal Proximity Sensing

Jiale Fan, Connor Flynn, Tianao Xu +4

Learning-based control has revolutionized dynamic locomotion, yet navigating unstructured terrain remains limited by a robot's incomplete awareness of imminent ground contact. Whil…

cs.RO2025

Constrained Style Learning from Imperfect Demonstrations under Task Optimality

Kehan Wen, Chenhao Li, Junzhe He +1

Learning from demonstration has proven effective in robotics for acquiring natural behaviors, such as stylistic motions and lifelike agility, particularly when explicitly defining…

cs.RO2025

Attention-Based Map Encoding for Learning Generalized Legged Locomotion

Junzhe He, Chong Zhang, Fabian Jenelten +3

Dynamic locomotion of legged robots is a critical yet challenging topic in expanding the operational range of mobile robots. It requires precise planning when possible footholds ar…

cs.RO2025

Parkour in the Wild: Learning a General and Extensible Agile Locomotion Policy Using Multi-expert Distillation and RL Fine-tuning

Nikita Rudin, Junzhe He, Joshua Aurand +1

Legged robots are well-suited for navigating terrains inaccessible to wheeled robots, making them ideal for applications in search and rescue or space exploration. However, current…