4 citations · 7 across the 9 of their papers we have counts for
9 papers
Humanoid Safe Stop via Learned Stoppability Value
Junfeng Long, Pieter Abbeel, Koushil Sreenath +3
Humanoid robots responding to emergency stop commands typically execute a fixed maneuver, without reasoning about whether a safe stop is actually feasible from the current state. W…
Towards Adaptable Humanoid Control via Adaptive Motion Tracking
Tao Huang, Huayi Wang, Junli Ren +8
Humanoid robots are envisioned to adapt demonstrated motions to diverse real-world conditions while accurately preserving motion patterns. Existing motion prior approaches enable w…
Humanoid Goalkeeper: Learning from Position Conditioned Task-Motion Constraints
Junli Ren, Junfeng Long, Tao Huang +7
We present a reinforcement learning framework for autonomous goalkeeping with humanoid robots in real-world scenarios. While prior work has demonstrated similar capabilities on qua…
Demonstrating Berkeley Humanoid Lite: An Open-source, Accessible, and Customizable 3D-printed Humanoid Robot
Yufeng Chi, Qiayuan Liao, Junfeng Long +5
Despite significant interest and advancements in humanoid robotics, most existing commercially available hardware remains high-cost, closed-source, and non-transparent within the r…
Learning Humanoid Locomotion with Perceptive Internal Model
Junfeng Long, Junli Ren, Moji Shi +4
In contrast to quadruped robots that can navigate diverse terrains using a "blind" policy, humanoid robots require accurate perception for stable locomotion due to their high degre…
GRUtopia: Dream General Robots in a City at Scale
Hanqing Wang, Jiahe Chen, Wensi Huang +19
Recent works have been exploring the scaling laws in the field of Embodied AI. Given the prohibitive costs of collecting real-world data, we believe the Simulation-to-Real (Sim2Rea…
TOP-Nav: Legged Navigation Integrating Terrain, Obstacle and Proprioception Estimation
Junli Ren, Yikai Liu, Yingru Dai +2
Legged navigation is typically examined within open-world, off-road, and challenging environments. In these scenarios, estimating external disturbances requires a complex synthesis…
Learning H-Infinity Locomotion Control
Junfeng Long, Wenye Yu, Quanyi Li +3
Stable locomotion in precipitous environments is an essential task for quadruped robots, requiring the ability to resist various external disturbances. Recent neural policies enhan…
Hybrid Internal Model: Learning Agile Legged Locomotion with Simulated Robot Response
Junfeng Long, Zirui Wang, Quanyi Li +3
Robust locomotion control depends on accurate state estimations. However, the sensors of most legged robots can only provide partial and noisy observations, making the estimation p…