43 citations · 118 across the 9 of their papers we have counts for
9 papers
Demonstrating Mobile Manipulation in the Wild: A Metrics-Driven Approach
Max Bajracharya, James Borders, Richard Cheng +11
We present our general-purpose mobile manipulation system consisting of a custom robot platform and key algorithms spanning perception and planning. To extensively test the system…
AutoBag: Learning to Open Plastic Bags and Insert Objects
Lawrence Yunliang Chen, Baiyu Shi, Daniel Seita +4
Thin plastic bags are ubiquitous in retail stores, healthcare, food handling, recycling, homes, and school lunchrooms. They are challenging both for perception (due to specularitie…
SGTM 2.0: Autonomously Untangling Long Cables using Interactive Perception
Kaushik Shivakumar, Vainavi Viswanath, Anrui Gu +6
Cables are commonplace in homes, hospitals, and industrial warehouses and are prone to tangling. This paper extends prior work on autonomously untangling long cables by introducing…
Efficiently Learning Single-Arm Fling Motions to Smooth Garments
Lawrence Yunliang Chen, Huang Huang, Ellen Novoseller +6
Recent work has shown that 2-arm "fling" motions can be effective for garment smoothing. We consider single-arm fling motions. Unlike 2-arm fling motions, which require little robo…
Limits of Probabilistic Safety Guarantees when Considering Human Uncertainty
Richard Cheng, Richard M. Murray, Joel W. Burdick
When autonomous robots interact with humans, such as during autonomous driving, explicit safety guarantees are crucial in order to avoid potentially life-threatening accidents. Man…
Safe Multi-Agent Interaction through Robust Control Barrier Functions with Learned Uncertainties
Richard Cheng, Mohammad Javad Khojasteh, Aaron D. Ames +1
Robots operating in real world settings must navigate and maintain safety while interacting with many heterogeneous agents and obstacles. Multi-Agent Control Barrier Functions (CBF…
Human Preference-Based Learning for High-dimensional Optimization of Exoskeleton Walking Gaits
Maegan Tucker, Myra Cheng, Ellen Novoseller +4
Optimizing lower-body exoskeleton walking gaits for user comfort requires understanding users' preferences over a high-dimensional gait parameter space. However, existing preferenc…
Control Regularization for Reduced Variance Reinforcement Learning
Richard Cheng, Abhinav Verma, Gabor Orosz +3
Dealing with high variance is a significant challenge in model-free reinforcement learning (RL). Existing methods are unreliable, exhibiting high variance in performance from run t…
End-to-End Safe Reinforcement Learning through Barrier Functions for Safety-Critical Continuous Control Tasks
Richard Cheng, Gabor Orosz, Richard M. Murray +1
Reinforcement Learning (RL) algorithms have found limited success beyond simulated applications, and one main reason is the absence of safety guarantees during the learning process…