75 citations · 285 across the 48 of their papers we have counts for
56 papers
Learning Robot Policies for Whole-Body Mobility Assistance via Dynamic Human Motion Generation
Shikun Ban, Shohei Nagai, Qingyang Song +4
Robotic assistance for human mobility could benefit care recipients and reduce caregiver burden during physically demanding tasks such as Sit-to-Stand (STS) and Lift-and-Transfer (…
BlenDAgger: Blended Shared Control for Interactive Imitation Learning
Cailyn Smith, Geoffrey Sun, Henny Admoni +1
Robot policies are frequently trained from human corrections, yet teleoperating a robot to provide corrections is burdensome, and human demonstrators are not always optimal. We pro…
An Empirical Study on What Matters for Viewpoint-Generalizable Policies in Visual Imitation Learning
Mino Nakura, Sriram Krishna, Yufei Wang +3
Visual imitation learning is a promising approach to training robot manipulation policies capable of completing a wide variety of tasks. However, policies today remain brittle to v…
SeeQ: Training Generalist Value Functions for Long-Horizon Robotic Manipulation
Saksham Singh, Zheyuan Hu, Max Sobol Mark +3
Despite rapid progress, generalist robot policies remain brittle on complex, long-horizon tasks that comprise multiple stages or require repeated attempts and deliberation on the s…
: Training Robots to Reason in Natural Language via Reinforcement Learning
Lehong Wu, Yuxiao Qu, Zheyuan Hu +4
Reasoning in language allows foundation models to spend more test-time compute on hard problems, such as those requiring decomposition, constraint tracking, and prediction of futur…
Bimanual High-Density EMG Control for In-Home Mobile Manipulation by Users with Quadriplegia
Jehan Yang, Eleanor Hodgson, Cindy Sun +2
Mobile manipulators in the home can enable people with cervical spinal cord injury (cSCI) to perform daily physical household tasks that they could not otherwise do themselves. How…
Force-Modulated Visual Policy for Robot-Assisted Dressing with Arm Motions
Alexis Yihong Hao, Yufei Wang, Navin Sriram Ravie +3
Robot-assisted dressing has the potential to significantly improve the lives of individuals with mobility impairments. To ensure an effective and comfortable dressing experience, t…
Geometric Red-Teaming for Robotic Manipulation
Divyam Goel, Yufei Wang, Tiancheng Wu +4
Standard evaluation protocols in robotic manipulation typically assess policy performance over curated, in-distribution test sets, offering limited insight into how systems fail un…
ArticuBot: Learning Universal Articulated Object Manipulation Policy via Large Scale Simulation
Yufei Wang, Ziyu Wang, Mino Nakura +5
This paper presents ArticuBot, in which a single learned policy enables a robotics system to open diverse categories of unseen articulated objects in the real world. This task has…
Towards Wearable Interfaces for Robotic Caregiving
Akhil Padmanabha, Carmel Majidi, Zackory Erickson
Physically assistive robots in home environments can enhance the autonomy of individuals with impairments, allowing them to regain the ability to conduct self-care and household ta…
LAMS: LLM-Driven Automatic Mode Switching for Assistive Teleoperation
Yiran Tao, Jehan Yang, Dan Ding +1
Teleoperating high degrees-of-freedom (DoF) robotic manipulators via low-DoF controllers like joysticks often requires frequent switching between control modes, where each mode map…
EMGBench: Benchmarking Out-of-Distribution Generalization and Adaptation for Electromyography
Jehan Yang, Maxwell Soh, Vivianna Lieu +2
This paper introduces the first generalization and adaptation benchmark using machine learning for evaluating out-of-distribution performance of electromyography (EMG) classificati…
Real-World Offline Reinforcement Learning from Vision Language Model Feedback
Sreyas Venkataraman, Yufei Wang, Ziyu Wang +3
Offline reinforcement learning can enable policy learning from pre-collected, sub-optimal datasets without online interactions. This makes it ideal for real-world robots and safety…
Towards an LLM-Based Speech Interface for Robot-Assisted Feeding
Jessie Yuan, Janavi Gupta, Akhil Padmanabha +4
Physically assistive robots present an opportunity to significantly increase the well-being and independence of individuals with motor impairments or other forms of disability who…
Incremental Learning for Robot Shared Autonomy
Yiran Tao, Guixiu Qiao, Dan Ding +1
Shared autonomy holds promise for improving the usability and accessibility of assistive robotic arms, but current methods often rely on costly expert demonstrations and remain sta…
Do Mistakes Matter? Comparing Trust Responses of Different Age Groups to Errors Made by Physically Assistive Robots
Sasha Wald, Kavya Puthuveetil, Zackory Erickson
Trust is a key factor in ensuring acceptable human-robot interaction, especially in settings where robots may be assisting with critical activities of daily living. When practicall…
Unfolding the Literature: A Review of Robotic Cloth Manipulation
Alberta Longhini, Yufei Wang, Irene Garcia-Camacho +9
The realm of textiles spans clothing, households, healthcare, sports, and industrial applications. The deformable nature of these objects poses unique challenges that prior work on…
RoboCAP: Robotic Classification and Precision Pouring of Diverse Liquids and Granular Media with Capacitive Sensing
Yexin Hu, Alexandra Gillespie, Akhil Padmanabha +4
Liquids and granular media are pervasive throughout human environments, yet remain particularly challenging for robots to sense and manipulate precisely. In this work, we present a…
SkinGrip: An Adaptive Soft Robotic Manipulator with Capacitive Sensing for Whole-Limb Bed Bathing Assistance
Fukang Liu, Kavya Puthuveetil, Akhil Padmanabha +3
Robotics presents a promising opportunity for enhancing bathing assistance, potentially to alleviate labor shortages and reduce care costs, while offering consistent and gentle car…
BodyMAP -- Jointly Predicting Body Mesh and 3D Applied Pressure Map for People in Bed
Abhishek Tandon, Anujraaj Goyal, Henry M. Clever +1
Accurately predicting the 3D human posture and the pressure exerted on the body for people resting in bed, visualized as a body mesh (3D pose & shape) with a 3D pressure map, holds…
VoicePilot: Harnessing LLMs as Speech Interfaces for Physically Assistive Robots
Akhil Padmanabha, Jessie Yuan, Janavi Gupta +4
Physically assistive robots present an opportunity to significantly increase the well-being and independence of individuals with motor impairments or other forms of disability who…
AdaFold: Adapting Folding Trajectories of Cloths via Feedback-loop Manipulation
Alberta Longhini, Michael C. Welle, Zackory Erickson +1
We present AdaFold, a model-based feedback-loop framework for optimizing folding trajectories. AdaFold extracts a particle-based representation of cloth from RGB-D images and feeds…
DiffTORI: Differentiable Trajectory Optimization for Deep Reinforcement and Imitation Learning
Weikang Wan, Ziyu Wang, Yufei Wang +2
This paper introduces DiffTORI, which utilizes Differentiable Trajectory Optimization as the policy representation to generate actions for deep Reinforcement and Imitation learning…
RL-VLM-F: Reinforcement Learning from Vision Language Foundation Model Feedback
Yufei Wang, Zhanyi Sun, Jesse Zhang +4
Reward engineering has long been a challenge in Reinforcement Learning (RL) research, as it often requires extensive human effort and iterative processes of trial-and-error to desi…