1 citations · 2 across the 6 of their papers we have counts for
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Navigation Explainability for Object Avoidance with LLMs for Assistive Robots
Courtney Young, Yi Lian, Taery Kim +1
Blind and visually impaired individuals face uncertainty when navigating unfamiliar areas. Whether a cane or a guide dog is used for navigation, this may prove to be challenging. T…
CF-JEPA: Improving Robustness of JEPA World Models via Controllability Factorization
Morgan Byrd, Robert Wright, Sehoon Ha
Controlling an agent with vision requires being able to separate useful information from irrelevant background information. JEPA-style latent world models seem like a natural appro…
Dynamic Policy Learning for Legged Robot with Simplified Model Pretraining and Model-Homotopy-Inspired Transfer
Dongyun Kang, Min-Gyu Kim, Tae-Gyu Song +3
Generating dynamic motions for legged robots remains a challenging problem. While reinforcement learning has achieved notable success in various legged locomotion tasks, producing…
Learning a High-quality Robotic Wiping Policy Using Systematic Reward Analysis and Visual-Language Model Based Curriculum
Yihong Liu, Dongyeop Kang, Sehoon Ha
Autonomous robotic wiping is an important task in various industries, ranging from industrial manufacturing to sanitization in healthcare. Deep reinforcement learning (Deep RL) has…
PrivilegedDreamer: Explicit Imagination of Privileged Information for Rapid Adaptation of Learned Policies
Morgan Byrd, Jackson Crandell, Mili Das +3
Numerous real-world control problems involve dynamics and objectives affected by unobservable hidden parameters, ranging from autonomous driving to robotic manipulation, which caus…
Understanding Expectations for a Robotic Guide Dog for Visually Impaired People
J. Taery Kim, Morgan Byrd, Jack L. Crandell +3
Robotic guide dogs hold significant potential to enhance the autonomy and mobility of blind or visually impaired (BVI) individuals by offering universal assistance over unstructure…