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cs.RO2026

More Structure, Not More Capacity: Object-Centric Representations for Visuomotor Imitation Learning

Yi Li, Alexandre Chapin, Liming Chen +2

Robotic manipulation policies rely on pre-trained vision models that give either a global scene embedding or a dense patch grid. Both mix task-relevant and task-irrelevant features…

cs.RO2026

STORM: Slot-based Task-aware Object-centric Representation for robotic Manipulation

Alexandre Chapin, Emmanuel Dellandréa, Liming Chen

Visual foundation models provide strong perceptual features for robotics, but their dense representations lack explicit object-level structure, limiting robustness and controllabil…

cs.RO2026

Spotlighting Task-Relevant Features: Object-Centric Representations for Better Generalization in Robotic Manipulation

Alexandre Chapin, Bruno Machado, Emmanuel Dellandréa +1

The generalization capabilities of robotic manipulation policies are heavily influenced by the choice of visual representations. Existing approaches typically rely on representatio…

cs.RO2026

Flowing With Purpose: Latent Action Guided Flow Matching Policies For Robotic Manipulation

Bruno Machado, Alexandre Chapin, Emmanuel Dellandrea +1

Flow matching has recently become a new standard for behavior cloning in robotic manipulation. However, state-of-the-art flow matching policies suffer from a systematic structural…

cs.RO2026

Warm-Starting Collision-Free Model Predictive Control With Object-Centric Diffusion

Arthur Haffemayer, Alexandre Chapin, Armand Jordana +4

Acting in cluttered environments requires predicting and avoiding collisions while still achieving precise control. Conventional optimization-based controllers can enforce physical…

cs.RO2025

Robotic Manipulation via Imitation Learning: Taxonomy, Evolution, Benchmark, and Challenges

Zezeng Li, Alexandre Chapin, Enda Xiang +6

Robotic Manipulation (RM) is central to the advancement of autonomous robots, enabling them to interact with and manipulate objects in real-world environments. This survey focuses…