6 papers
SC3-Eval: Evaluating Robot Foundation Models via Self-Consistent Video Generation
Wei-Cheng Tseng, Gashon Hussein, Yuzhu Dong +9
Evaluating generalist robot manipulation policies in the real world is expensive, slow, and difficult to scale. Action-conditioned video world models offer a scalable alternative b…
TAM: Torque Adaptation Module for Robust Motion Transfer in Manipulation
Dongwon Son, Florian Shkurti, Jason Lee +3
A policy tuned for one robot often behaves differently on another, whether due to the sim-to-real gap, unknown payloads, or the differing dynamics of two instances of the same robo…
Automated Planning Domain Inference for Task and Motion Planning
Jinbang Huang, Allen Tao, Rozilyn Marco +3
Task and motion planning (TAMP) frameworks address long and complex planning problems by integrating high-level task planners with low-level motion planners. However, existing TAMP…
SICNav-Diffusion: Safe and Interactive Crowd Navigation with Diffusion Trajectory Predictions
Sepehr Samavi, Anthony Lem, Fumiaki Sato +5
To navigate crowds without collisions, robots must interact with humans by forecasting their future motion and reacting accordingly. While learning-based prediction models have sho…
Deploying SICNav in the Field: Safe and Interactive Crowd Navigation using MPC and Bilevel Optimization
Sepehr Samavi, Garvish Bhutani, Florian Shkurti +1
Safe and efficient navigation in crowded environments remains a critical challenge for robots that provide a variety of service tasks such as food delivery or autonomous wheelchair…
SICNav: Safe and Interactive Crowd Navigation using Model Predictive Control and Bilevel Optimization
Sepehr Samavi, James R. Han, Florian Shkurti +1
Robots need to predict and react to human motions to navigate through a crowd without collisions. Many existing methods decouple prediction from planning, which does not account fo…