6 papers
FlowDPG: Deterministic Policy Gradient on Flow Matching Policies for Real-World Manipulation
Kexin Shi, Junyao Shi, Poorvi Hebbar +5
Real-world reinforcement learning for robotic manipulation remains challenging, and this difficulty is amplified for flow matching policies: applying policy gradient methods to the…
OmniGuide: Universal Guidance Fields for Enhancing Generalist Robot Policies
Yunzhou Song, Long Le, Yong-Hyun Park +7
Vision-language-action(VLA) models have shown great promise as generalist policies for a large range of relatively simple tasks. However, they demonstrate limited performance on mo…
Maestro: Orchestrating Robotics Modules with Vision-Language Models for Zero-Shot Generalist Robots
Junyao Shi, Rujia Yang, Kaitian Chao +9
Today's best-explored routes towards generalist robots center on collecting ever larger "observations-in actions-out" robotics datasets to train large end-to-end models, copying a…
VLMgineer: Vision Language Models as Robotic Toolsmiths
George Jiayuan Gao, Tianyu Li, Junyao Shi +4
Tool design and use reflect the ability to understand and manipulate the physical world through creativity, planning, and foresight. As such, these capabilities are often regarded…
ZeroMimic: Distilling Robotic Manipulation Skills from Web Videos
Junyao Shi, Zhuolun Zhao, Tianyou Wang +5
Many recent advances in robotic manipulation have come through imitation learning, yet these rely largely on mimicking a particularly hard-to-acquire form of demonstrations: those…
Don't Yell at Your Robot: Physical Correction as the Collaborative Interface for Language Model Powered Robots
Chuye Zhang, Yifei Simon Shao, Harshil Parekh +4
We present a novel approach for enhancing human-robot collaboration using physical interactions for real-time error correction of large language model (LLM) powered robots. Unlike…