arXiv AI
Learning Low-Frequency Motion Control for Robust and Dynamic Robot Locomotion
Read the original on arXiv AI →The Flow has not summarised this story yet — read it at arXiv AI.
Related stories
arXiv AI
Aug 10
Learning to Walk With Less: A Dyna-Style Approach to Quadrupedal Locomotion
arXiv:2509. 06296v2 Announce Type: replace-cross Abstract: Traditional on-policy reinforcement learning (RL) controllers for quadrupedal locomotion often suffer from low data efficiency, requiring millions of interactions with simulated environments to achieve stable control.
arXiv Machine Learning
Jul 23
Isaac Sim-to-Real: Reinforcement Learning based Locomotion for Quadrupeds
arXiv:2607. 18135v1 Announce Type: cross Abstract: Learning-based approaches to locomotion have risen in popularity in recent years, showing the capability for complex legged locomotion and whole-body control.
arXiv Machine Learning
Jul 23
Towards Torque-Driven Reinforcement Learning for Quadruped Locomotion
arXiv:2607. 18365v1 Announce Type: cross Abstract: Reinforcement learning (RL) for legged robots is advancing locomotion, demonstrating its ability to adapt to new and challenging terrain.
arXiv AI
Jul 16
Agile perceptive multi-skill locomotion for quadrupedal robots in the wild
arXiv:2607. 13579v1 Announce Type: cross Abstract: Enabling quadrupedal robots to traverse complex terrains-from rugged outdoor environments to urban landscapes-requires seamless integration of multiple motor skills, smooth transitions between gaits, and high-speed perceptive locomotion using only onboard sensors.
arXiv AI
Aug 13
Learning Loco-Manipulation From SMPC Demonstrations With Sparse Offline-to-Online RL
arXiv:2608. 12063v1 Announce Type: cross Abstract: Integrating locomotion and manipulation is essential for robot autonomy, but scaling standard Reinforcement Learning (RL) to complex tasks is severely bottlenecked by the slow, manual process of dense reward shaping.
arXiv Machine Learning
Aug 10
Learning Fault-Tolerant Locomotion with Adaptive Gait Timing
arXiv:2608. 07328v1 Announce Type: cross Abstract: Hardware failures require legged robots to rapidly reorganize coordination and gait timing to maintain stability and mobility.