17 citations · 79 across the 40 of their papers we have counts for
37 papers · 1 filter
Force-Aware Reinforcement Learning with Hybrid Sensorless Force Estimation for Wheeled-Legged Loco-Manipulation
Xuanqi Zeng, Jiaming Wang, Tianlin Zhang +5
Force-controlled loco-manipulation requires a whole-body policy to coordinate locomotion and arm motion while regulating end-effector interaction forces. This is challenging under…
RoboDojo: A Unified Sim-and-Real Benchmark for Comprehensive Evaluation of Generalist Robot Manipulation Policies
Tianxing Chen, Yue Chen, Zixuan Li +41
Generalist robot manipulation policies have advanced rapidly, yet existing benchmarks remain limited in systematically evaluating their capabilities. Many rely on simple, short-hor…
KEMO: Event-Driven Keyframe Memory for Long-Horizon Robot Manipulation with VLA Policies
Yihan Zeng, Minghao Ye, Yiyuan Chen +4
Long-horizon robot manipulation remains challenging because similar observations may occur at different execution stages, while the appropriate action depends on previously complet…
RoboNaldo: Accurate, Stable and Powerful Humanoid Soccer Shooting via Motion-Guided Curriculum Reinforcement Learning
Yichao Zhong, Yidan Lu, Yuhang Lu +9
Elite humanoid soccer shooting requires whole-body stability, high-impulse whole-body interactions, and accuracy to targets. Motion tracking-driven reinforcement learning (RL) prov…
VRA: Grounding Discrete-Time Joint Acceleration in Voltage-Constrained Actuation
Lingwei Zhang, Jiaming Wang, Tianlin Zhang +5
Discrete-time joint acceleration constraints are widely used to enforce position and velocity limits. However, under voltage-constrained electric actuators, kinematically admissibl…
Ego-Vision World Model for Humanoid Contact Planning
Hang Liu, Yuman Gao, Sangli Teng +5
Enabling humanoid robots to exploit physical contact, rather than simply avoid collisions, is crucial for autonomy in unstructured environments. Traditional optimization-based plan…
Toward Real-World Cooperative and Competitive Soccer with Quadrupedal Robot Teams
Zhi Su, Yuman Gao, Emily Lukas +8
Achieving coordinated teamwork among legged robots requires both fine-grained locomotion control and long-horizon strategic decision-making. Robot soccer offers a compelling testbe…
LangWBC: Language-directed Humanoid Whole-Body Control via End-to-end Learning
Yiyang Shao, Xiaoyu Huang, Bike Zhang +6
General-purpose humanoid robots are expected to interact intuitively with humans, enabling seamless integration into daily life. Natural language provides the most accessible mediu…
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…
Decentralized Navigation of a Cable-Towed Load using Quadrupedal Robot Team via MARL
Wen-Tse Chen, Minh Nguyen, Zhongyu Li +2
This work addresses the challenge of enabling a team of quadrupedal robots to collaboratively tow a cable-connected load through cluttered and unstructured environments while avoid…
Traversability-Aware Legged Navigation by Learning from Real-World Visual Data
Hongbo Zhang, Zhongyu Li, Xuanqi Zeng +9
The enhanced mobility brought by legged locomotion empowers quadrupedal robots to navigate through complex and unstructured environments. However, optimizing agile locomotion while…
Online Omnidirectional Jumping Trajectory Planning for Quadrupedal Robots on Uneven Terrains
Linzhu Yue, Zhitao Song, Jinhu Dong +6
Natural terrain complexity often necessitates agile movements like jumping in animals to improve traversal efficiency. To enable similar capabilities in quadruped robots, complex r…
Learning Smooth Humanoid Locomotion through Lipschitz-Constrained Policies
Zixuan Chen, Xialin He, Yen-Jen Wang +8
Reinforcement learning combined with sim-to-real transfer offers a general framework for developing locomotion controllers for legged robots. To facilitate successful deployment in…
Interactive Navigation with Adaptive Non-prehensile Mobile Manipulation
Cunxi Dai, Xiaohan Liu, Koushil Sreenath +2
This paper introduces a framework for interactive navigation through adaptive non-prehensile mobile manipulation. A key challenge in this process is handling objects with unknown d…
CurricuLLM: Automatic Task Curricula Design for Learning Complex Robot Skills using Large Language Models
Kanghyun Ryu, Qiayuan Liao, Zhongyu Li +3
Curriculum learning is a training mechanism in reinforcement learning (RL) that facilitates the achievement of complex policies by progressively increasing the task difficulty duri…
Berkeley Humanoid: A Research Platform for Learning-based Control
Qiayuan Liao, Bike Zhang, Xuanyu Huang +3
We introduce Berkeley Humanoid, a reliable and low-cost mid-scale humanoid research platform for learning-based control. Our lightweight, in-house-built robot is designed specifica…
HiLMa-Res: A General Hierarchical Framework via Residual RL for Combining Quadrupedal Locomotion and Manipulation
Xiaoyu Huang, Qiayuan Liao, Yiming Ni +5
This work presents HiLMa-Res, a hierarchical framework leveraging reinforcement learning to tackle manipulation tasks while performing continuous locomotion using quadrupedal robot…
DiffuseLoco: Real-Time Legged Locomotion Control with Diffusion from Offline Datasets
Xiaoyu Huang, Yufeng Chi, Ruofeng Wang +5
This work introduces DiffuseLoco, a framework for training multi-skill diffusion-based policies for dynamic legged locomotion from offline datasets, enabling real-time control of d…
Long-horizon Locomotion and Manipulation on a Quadrupedal Robot with Large Language Models
Yutao Ouyang, Jinhan Li, Yunfei Li +4
We present a large language model (LLM) based system to empower quadrupedal robots with problem-solving abilities for long-horizon tasks beyond short-term motions. Long-horizon tas…
Learning Visual Quadrupedal Loco-Manipulation from Demonstrations
Zhengmao He, Kun Lei, Yanjie Ze +3
Quadruped robots are progressively being integrated into human environments. Despite the growing locomotion capabilities of quadrupedal robots, their interaction with objects in re…
Leveraging Symmetry in RL-based Legged Locomotion Control
Zhi Su, Xiaoyu Huang, Daniel Ordoñez-Apraez +8
Model-free reinforcement learning is a promising approach for autonomously solving challenging robotics control problems, but faces exploration difficulty without information of th…
Reinforcement Learning for Versatile, Dynamic, and Robust Bipedal Locomotion Control
Zhongyu Li, Xue Bin Peng, Pieter Abbeel +3
This paper presents a comprehensive study on using deep reinforcement learning (RL) to create dynamic locomotion controllers for bipedal robots. Going beyond focusing on a single l…
Robust and Versatile Bipedal Jumping Control through Reinforcement Learning
Zhongyu Li, Xue Bin Peng, Pieter Abbeel +3
This work aims to push the limits of agility for bipedal robots by enabling a torque-controlled bipedal robot to perform robust and versatile dynamic jumps in the real world. We pr…
Walking in Narrow Spaces: Safety-critical Locomotion Control for Quadrupedal Robots with Duality-based Optimization
Qiayuan Liao, Zhongyu Li, Akshay Thirugnanam +2
This paper presents a safety-critical locomotion control framework for quadrupedal robots. Our goal is to enable quadrupedal robots to safely navigate in cluttered environments. To…