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Ergodic Control and Controlled Diffusion for Robot Learning: Review and Tutorial
Max Muchen Sun, Cem Bilaloglu, Ananya Rao +6
Diffusion learning leverages the statistical mechanism of diffusion processes for learning, reasoning, and inferring complex distributions from data. Recent advances in diffusion l…
Spline Policy: A Structured Representation for Robot Policies
Mengze Tian, Yiming Li, Sichao Liu +2
Modern imitation-learning policies for robot manipulation often represent actions as fixed-resolution action chunks, which are simple and effective but expose limited geometric and…
Physics-Informed Eikonal Caging for Whole-Arm Manipulation Planning
Yan Zhang, Yiming Li, Yifei Dong +2
Planning contact-rich whole-arm manipulation is challenging because interactions that involve extended robot geometry give rise to complex contact dynamics that are difficult to mo…
Ergodic Imitation for Adaptive Exploration around Demonstrations
Ziyi Xu, Cem Bilaloglu, Yiming Li +1
In robotics, a common challenge in imitation learning is the mismatch between training and deployment conditions, caused, for example, by environmental changes or imperfect observa…
Fast and Safe Trajectory Optimization for Mobile Manipulators With Neural Configuration Space Distance Field
Yulin Li, Zhiyuan Song, Yiming Li +8
Mobile manipulators promise agile, long-horizon behavior by coordinating base and arm motion, yet whole-body trajectory optimization in cluttered, confined spaces remains difficult…
Object-centric Task Representation and Transfer using Diffused Orientation Fields
Cem Bilaloglu, Tobias Löw, Sylvain Calinon
Curved objects pose a fundamental challenge for skill transfer in robotics: unlike planar surfaces, they do not admit a global reference frame. As a result, task-relevant direction…