arXiv AI August 18, 2026 By Linjin He, Xinda Qi, Dong Chen, Zhaojian Li, Xiaobo Tan

DiSA-IQL: Offline Reinforcement Learning for Robust Soft Robot Control under Distribution Shifts

arXiv:2510. 00358v2 Announce Type: replace-cross Abstract: Soft snake robots offer remarkable flexibility and adaptability in complex environments, yet their control remains challenging due to highly nonlinear dynamics.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

arXiv AI

Jun 15

Sensitivity Shaping for Latent Modeling

arXiv:2606. 14585v1 Announce Type: cross Abstract: Generative dynamics models enable planning in challenging robotic systems, but safe deployment requires reliably detecting policy-induced out-of-distribution (OOD) transitions.

By Hongzhan Yu, Chenghao Li, Ruipeng Zhang, Henrik Christensen, Sicun Gao

robotics

arXiv Machine Learning

Jul 1

Warp RL: Reshaping Base Policy Distributions for Dynamics Adaptation

arXiv:2606. 31043v1 Announce Type: new Abstract: Residual reinforcement learning adapts a pretrained robot policy by learning an additive correction to its actions.

By Ethan Hirschowitz, Fabio Ramos

reinforcement-learning robotics

arXiv AI

Jul 14

VINE: Taming Generative Control Policies for Reinforcement Learning

arXiv:2607. 10369v1 Announce Type: cross Abstract: Flow-matching policies have emerged as an effective policy parameterization for robot learning.

By Rushuai Yang, Zhuo Han, Houlin Li, Hecheng Wang, Zhichao Wu, Rui Zhang, Zhaowei Zhang, Zihong Chen, Xiaohan Yan, Chiming Liu, Yi Chen, Wei Shan, Maoqing Yao

reinforcement-learning robotics multimodal benchmarks

arXiv AI

Jul 29

A context-adaptive policy framework for robust and reactive robotic manipulation via uncertainty-aware imitation learning

arXiv:2410. 24035v2 Announce Type: replace-cross Abstract: Generating robust and reactive manipulation strategies that can adapt to changing context information is a challenging task in robotics.

By Tim R. Winter, Leonard Kl\"upfel, Ashok M. Sundaram, Werner Friedl, Maximo A. Roa, Freek Stulp, Jo\~ao Silv\'erio

robotics benchmarks

arXiv Machine Learning

Jun 10

MODIP: Efficient Model-Based Optimization for Diffusion Policies

arXiv:2606. 10825v1 Announce Type: new Abstract: Diffusion policies (DPs) have emerged as expressive policy representations for robot learning, often used with imitation learning methods such as behavioral cloning (BC).

By Zakariae El Asri, Philippe Gratias-Quiquandon, Nicolas Thome, Olivier Sigaud

diffusion reinforcement-learning robotics fine-tuning

arXiv AI

Jun 17

When Life Gives You BC, Make Q-functions: Extracting Q-values from Behavior Cloning for On-Robot Reinforcement Learning

arXiv:2605. 05172v2 Announce Type: replace-cross Abstract: Behavior Cloning (BC) has emerged as a highly effective paradigm for robot learning.

By Lakshita Dodeja, Ondrej Biza, Shivam Vats, Stephen Hart, Stefanie Tellex, Robin Walters, Karl Schmeckpeper, Thomas Weng

reinforcement-learning robotics benchmarks

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Sensitivity Shaping for Latent Modeling

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VINE: Taming Generative Control Policies for Reinforcement Learning

A context-adaptive policy framework for robust and reactive robotic manipulation via uncertainty-aware imitation learning

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