Learning Agent-Aware Affordances for Closed-Loop Interaction with Articulated Objects

Author:

Schiavi Giulio1,Wulkop Paula1,Rizzi Giuseppe1,Ott Lionel1,Siegwart Roland1,Chung Jen Jen1

Affiliation:

1. ETH,Autonomous Systems Lab,Zurich,Switzerland

Publisher

IEEE

Reference41 articles.

1. Operating articulated objects based on experience

2. Kineverse: A Symbolic Articulation Model Framework for Model-Agnostic Mobile Manipulation

3. A Transition-Aware Method for the Simulation of Compliant Contact With Regularized Friction

4. Learning Hybrid Object Kinematics for Effi-cient Hierarchical Planning Under Uncertainty;jain;Proc of the IEEE/RSJ Int Conf on Intelligent Robots and Systems (IROS),0

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1. Articulated Object Manipulation with Coarse-to-fine Affordance for Mitigating the Effect of Point Cloud Noise;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

2. SM3: Self-supervised Multi-task Modeling with Multi-view 2D Images for Articulated Objects;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

3. Language-Conditioned Affordance-Pose Detection in 3D Point Clouds;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

4. Online Estimation of Articulated Objects with Factor Graphs using Vision and Proprioceptive Sensing;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

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