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cs.RO2025

Learning to Throw-Flip

Yang Liu, Bruno Da Costa, Aude Billard

Dynamic manipulation, such as robot tossing or throwing objects, has recently gained attention as a novel paradigm to speed up logistic operations. However, the focus has predomina…

cs.RO2025

Imitation-Guided Bimanual Planning for Stable Manipulation under Changing External Forces

Kuanqi Cai, Chunfeng Wang, Zeqi Li +5

Robotic manipulation in dynamic environments often requires seamless transitions between different grasp types to maintain stability and efficiency. However, achieving smooth and a…

cs.RO2025

A roadmap for AI in robotics

Aude Billard, Alin Albu-Schaeffer, Michael Beetz +8

AI technologies, including deep learning, large-language models have gone from one breakthrough to the other. As a result, we are witnessing growing excitement in robotics at the p…

cs.RO2025

Implicit Articulated Robot Morphology Modeling with Configuration Space Neural Signed Distance Functions

Yiting Chen, Xiao Gao, Kunpeng Yao +3

In this paper, we introduce a novel approach to implicitly encode precise robot morphology using forward kinematics based on a configuration space signed distance function. Our pro…

cs.RO2025

Dexterous Cable Manipulation: Taxonomy, Multi-Fingered Hand Design, and Long-Horizon Manipulation

Sun Zhaole, Xiao Gao, Xiaofeng Mao +3

Existing research that addressed cable manipulation relied on two-fingered grippers, which make it difficult to perform similar cable manipulation tasks that humans perform. Howeve…

cs.RO2025

Positive-Unlabeled Constraint Learning for Inferring Nonlinear Continuous Constraints Functions from Expert Demonstrations

Baiyu Peng, Aude Billard

Planning for diverse real-world robotic tasks necessitates to know and write all constraints. However, instances exist where these constraints are either unknown or challenging to…