3 papers
cs.RO2025
APEX: Action Priors Enable Efficient Exploration for Robust Motion Tracking on Legged Robots
Shivam Sood, Laukik Nakhwa, Sun Ge +7
Learning natural, animal-like locomotion from demonstrations has become a core paradigm in legged robotics. Despite the recent advancements in motion tracking, most existing method…
cs.RO2025
STEP Planner: Constructing cross-hierarchical subgoal tree as an embodied long-horizon task planner
Tianxing Zhou, Zhirui Wang, Haojia Ao +5
The ability to perform reliable long-horizon task planning is crucial for deploying robots in real-world environments. However, directly employing Large Language Models (LLMs) as a…
cs.RO2025
SATA: Safe and Adaptive Torque-Based Locomotion Policies Inspired by Animal Learning
Peizhuo Li, Hongyi Li, Ge Sun +7
Despite recent advances in learning-based controllers for legged robots, deployments in human-centric environments remain limited by safety concerns. Most of these approaches use p…