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20212026
most citedTrustworthy Reinforcement Learning Against Intrinsic Vulnerabilities: Robustness, Safety, and Generalizability

19 citations · 39 across the 13 of their papers we have counts for

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5 papers · 1 filter

cs.RO2026

MIRROR: Reflecting Hidden Symmetries from Offline Robot Interaction Data

Shiqi Liu, Yihang Yao, Peide Huang +2

Symmetry-aware robot policy learning requires coupled observation-action transformations. For pixel observations, even simple physical symmetries can induce complex, viewpoint-depe…

cs.RO2024

Dynamics as Prompts: In-Context Learning for Sim-to-Real System Identifications

Xilun Zhang, Shiqi Liu, Peide Huang +4

Sim-to-real transfer remains a significant challenge in robotics due to the discrepancies between simulated and real-world dynamics. Traditional methods like Domain Randomization o…

cs.RO2024★ 1 cited

CaDRE: Controllable and Diverse Generation of Safety-Critical Driving Scenarios using Real-World Trajectories

Peide Huang, Wenhao Ding, Benjamin Stoler +3

Simulation is an indispensable tool in the development and testing of autonomous vehicles (AVs), offering an efficient and safe alternative to road testing. An outstanding challeng…

cs.RO2023★ 3 cited

Creative Robot Tool Use with Large Language Models

Mengdi Xu, Peide Huang, Wenhao Yu +7

Tool use is a hallmark of advanced intelligence, exemplified in both animal behavior and robotic capabilities. This paper investigates the feasibility of imbuing robots with the ab…

cs.RO2023★ 4 cited

What Went Wrong? Closing the Sim-to-Real Gap via Differentiable Causal Discovery

Peide Huang, Xilun Zhang, Ziang Cao +6

Training control policies in simulation is more appealing than on real robots directly, as it allows for exploring diverse states in an efficient manner. Yet, robot simulators inev…