Search Results - "Wang, Austin S."

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  1. 1

    Efficient and Interpretable Robot Manipulation With Graph Neural Networks by Lin, Yixin, Wang, Austin S., Undersander, Eric, Rai, Akshara

    Published in IEEE robotics and automation letters (01-04-2022)
    “…Manipulation tasks, like loading a dishwasher, can be seen as a sequence of spatial constraints and relationships between different objects. We aim to discover…”
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    Journal Article
  2. 2

    Learning State-Dependent Losses for Inverse Dynamics Learning by Morse, Kristen, Das, Neha, Lin, Yixin, Wang, Austin S., Rai, Akshara, Meier, Franziska

    “…Being able to quickly adapt to changes in dynamics is paramount in model-based control for object manipulation tasks. In order to influence fast adaptation of…”
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    Conference Proceeding
  3. 3

    Homography-Based Deep Visual Servoing Methods for Planar Grasps by Wang, Austin S., Zhang, Wuming, Troniak, Daniel, Liang, Jacky, Kroemer, Oliver

    “…We propose a visual servoing framework for learning to improve grasps of objects. RGB and depth images from grasp attempts are collected using an automated…”
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    Conference Proceeding
  4. 4

    Learning Robust Manipulation Strategies with Multimodal State Transition Models and Recovery Heuristics by Wang, Austin S., Kroemer, Oliver

    “…Robots are prone to making mistakes when performing manipulation tasks in unstructured environments. Robust policies are thus needed to not only avoid mistakes…”
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    Conference Proceeding
  5. 5

    Efficient and Interpretable Robot Manipulation with Graph Neural Networks by Lin, Yixin, Wang, Austin S, Undersander, Eric, Rai, Akshara

    Published 25-02-2021
    “…Manipulation tasks, like loading a dishwasher, can be seen as a sequence of spatial constraints and relationships between different objects. We aim to discover…”
    Get full text
    Journal Article
  6. 6

    Learning State-Dependent Losses for Inverse Dynamics Learning by Morse, Kristen, Das, Neha, Lin, Yixin, Wang, Austin S, Rai, Akshara, Meier, Franziska

    Published 14-08-2020
    “…Being able to quickly adapt to changes in dynamics is paramount in model-based control for object manipulation tasks. In order to influence fast adaptation of…”
    Get full text
    Journal Article
  7. 7

    Encoding Physical Constraints in Differentiable Newton-Euler Algorithm by Sutanto, Giovanni, Wang, Austin S, Lin, Yixin, Mukadam, Mustafa, Sukhatme, Gaurav S, Rai, Akshara, Meier, Franziska

    Published 23-01-2020
    “…Proceedings of the 2nd Conference on Learning for Dynamics and Control, PMLR 120:804-813, 2020 The recursive Newton-Euler Algorithm (RNEA) is a popular…”
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    Journal Article