1 citations · 1 across the 8 of their papers we have counts for
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Opt2VLA: Force-Aware Vision-Language-Action for Contact-Rich Humanoid Whole-Body Manipulation
Fukang Liu, Yipu Chen, Jaehwi Jang +3
Humanoid robots are expected to perform diverse human-level tasks in daily environments, many of which require precise regulation of interaction forces. While recent vision-languag…
Function-Space Diffusion for Motion Planning
Zinuo Chang, Yipu Chen, Byoungwoo Park +2
Diffusion-based motion planners have demonstrated strong performance in generating diverse and high-quality robot trajectories in cluttered environments with multiple feasible solu…
VQActFlow: Vector-Quantized Action Mode Steering for Multi-Task Robot Manipulation
Zhigen Zhao, Mark Leggiero, Yipu Chen +5
Multi-task robot manipulation policies are challenging to learn from demonstration because traditionally a single network must select among qualitatively different action modes fro…
REFINE-DP: Diffusion Policy Fine-tuning for Humanoid Loco-manipulation via Reinforcement Learning
Zhaoyuan Gu, Yipu Chen, Zimeng Chai +11
Humanoid loco-manipulation requires coordinated task-space motion planning with stable loco-manipulation command tracking under complex robot-environment dynamics and long-horizon…
Robust-Locomotion-by-Logic: Perturbation-Resilient Bipedal Locomotion via Signal Temporal Logic Guided Model Predictive Control
Zhaoyuan Gu, Yuntian Zhao, Yipu Chen +4
This study introduces a robust planning framework that utilizes a model predictive control (MPC) approach, enhanced by incorporating signal temporal logic (STL) specifications. Thi…
Signal Temporal Logic-Guided Model Predictive Control for Robust Bipedal Locomotion Resilient to Runtime External Perturbations
Zhaoyuan Gu, Rongming Guo, William Yates +2
This study investigates formal-method-based trajectory optimization (TO) for bipedal locomotion, focusing on scenarios where the robot encounters external perturbations at unforese…