6 papers · 1 filter
PLUME: Probabilistic Latent Unified World Modeling and Parameter Estimation for Multi-Finger Manipulation
Abhinav Kumar, Soshi Iba, Rana Soltani Zarrin +1
Dexterous manipulation with multi-finger hands can be sensitive to physical parameters such as object shape, pose, and friction coefficients. While simulation enables large-scale d…
CADRE: Dynamic Catching via Implicit Contact Descriptors and Task-Appropriate Recovery Affordances
Fan Yang, Zixuan Huang, Abhinav Kumar +4
Real-world dexterous manipulation often encounters unexpected errors and disturbances, which can lead to catastrophic failures, such as dropping the manipulated object. To address…
AVO: Amortized Value Optimization for Contact Mode Switching in Multi-Finger Manipulation
Adam Hung, Fan Yang, Abhinav Kumar +4
Dexterous manipulation tasks often require switching between different contact modes, such as rolling, sliding, sticking, or non-contact contact modes. When formulating dexterous m…
Diffusing Trajectory Optimization Problems for Recovery During Multi-Finger Manipulation
Abhinav Kumar, Fan Yang, Sergio Aguilera Marinovic +3
Multi-fingered hands are emerging as powerful platforms for performing fine manipulation tasks, including tool use. However, environmental perturbations or execution errors can imp…
Diffusion-Informed Probabilistic Contact Search for Multi-Finger Manipulation
Abhinav Kumar, Thomas Power, Fan Yang +4
Planning contact-rich interactions for multi-finger manipulation is challenging due to the high-dimensionality and hybrid nature of dynamics. Recent advances in data-driven methods…
Constraining Gaussian Process Implicit Surfaces for Robot Manipulation via Dataset Refinement
Abhinav Kumar, Peter Mitrano, Dmitry Berenson
Model-based control faces fundamental challenges in partially-observable environments due to unmodeled obstacles. We propose an online learning and optimization method to identify…