Robotics and embodied AI

Manipulation, locomotion, sim-to-real transfer and autonomous driving: learning systems that have to survive physics.

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arXiv AI

Jun 10

RoboNaldo: Accurate, Stable and Powerful Humanoid Soccer Shooting via Motion-Guided Curriculum Reinforcement Learning

arXiv:2606. 11092v1 Announce Type: cross Abstract: Elite humanoid soccer shooting requires whole-body stability, high-impulse whole-body interactions, and accuracy to targets.

By Yichao Zhong, Yidan Lu, Yuhang Lu, Tianyang Tang, Haoguang Mai, Yixuan Pan, Tianyu Li, Li Chen, Jingbo Wang, Zhongyu Li, Peng Lu, Hongyang Li

reinforcement-learning robotics

arXiv Machine Learning

Jun 10

Embodiment-conditioned Generalist Control for Multirotor Aerial Robots

arXiv:2606. 10857v1 Announce Type: cross Abstract: We present a generalist position control policy capable of controlling arbitrary multirotor configurations of a certain rotor count (e.

By Orestis Konstantaropoulos, Welf Rehberg, Mihir Kulkarni, Kostas Alexis

robotics

arXiv Machine Learning

Jun 10

On the Controllability-Fidelity Frontier in Diffusion Editing

arXiv:2606. 09901v1 Announce Type: cross Abstract: Diffusion-based generative models enable powerful image editing capabilities, but achieving precise control while maintaining fidelity and safety remains challenging.

By Yi Hu, Leying Yi, Emily Davis, Finn Carter

diffusion robotics benchmarks safety

arXiv AI

Jun 10

TaCarla: A comprehensive benchmarking dataset for end-to-end autonomous driving

arXiv:2602. 23499v4 Announce Type: replace-cross Abstract: Collecting a high-quality dataset is a critical task that demands meticulous attention to detail, as overlooking certain aspects can render the entire dataset unusable.

By Tugrul Gorgulu, Atakan Dag, M. Esat Kalfaoglu, Halil Ibrahim Kuru, Baris Can Cam, Halil Ibrahim Ozturk, Ozsel Kilinc

agents computer-vision robotics benchmarks

arXiv AI

Jun 10

Test-Time Gradient Guidance of Flow Policies in Reinforcement Learning

arXiv:2606. 11087v1 Announce Type: cross Abstract: Expressive continuous control policies, such as diffusion and flow models, form the backbone of recent advances in scaling imitation learning for simulated and real robot control.

By Zhiyuan Zhou, Andy Peng, Charles Xu, Qiyang Li, Tobias Springenberg, Kevin Frans, Sergey Levine

diffusion reinforcement-learning robotics benchmarks

arXiv AI

Jun 10

A Survey of Robotic Navigation and Manipulation with Physics Simulators in the Era of Embodied AI

arXiv:2505. 01458v2 Announce Type: replace-cross Abstract: Navigation and manipulation are core capabilities in Embodied AI, but training agents to perform them directly in the real world is costly, time-consuming, and unsafe.

By Lik Hang Kenny Wong, Xueyang Kang, Kaixin Bai, Jianwei Zhang

agents robotics benchmarks

arXiv AI

Jun 10

Beyond APIs: Probing the Limits of MLLMs in Physical Tool Use

arXiv:2606. 10803v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) excel at utilizing digital APIs and increasingly serve as the "brain" of embodied AI, instructing robots to interact with the physical world.

By Zhixin Ma, Yutong Zhou, Yongqi Li, Chong-Wah Ngo, Wenjie Li

llms agents robotics multimodal benchmarks

arXiv AI

Jun 10

A Practical Recipe Towards Improving Sim-and-Real Correlation for VLA Evaluation

arXiv:2606. 10366v1 Announce Type: cross Abstract: Simulation has become an essential tool for evaluating and improving vision-language-action (VLA) policies, offering scalable, reproducible, and controllable alternatives to costly real-world robot evaluation.

By Shuo Wang, Hanyuan Xu, Yingdong Hu, Fanqi Lin, Yang Gao

robotics fine-tuning multimodal benchmarks safety

arXiv AI

Jun 10

YUBI: Yielding Universal Bidigital Interface for Bimanual Dexterous Manipulation at Scale

arXiv:2606. 10244v1 Announce Type: cross Abstract: We introduce Yielding Universal Bidigital Interface (YUBI), a finger-aligned gripper designed to enable intuitive, ergonomic, and scalable data collection for bimanual dexterous manipulation.

By Takehiko Ohkawa, Jumpei Arima, Yuki Noguchi, Masatoshi Tateno, Makoto Sugiura, Takuya Okubo, Kengo Ikeuchi, Yuma Shin, Hiroki Nishizawa, Naoaki Kanazawa, Yuki Wakayama, Daiki Fukunaga, Koshi Makihara, Tomohiro Motoda, Floris Erich, Yukiyasu Domae, Tatsuya Matsushima, Yohishiro Okumatsu, Kei Ota

robotics

arXiv Machine Learning

Jun 10

Dexterous Point Policy: Learning Point-based Dexterous Hand Policies from Human Demonstrations

arXiv:2606. 10614v1 Announce Type: cross Abstract: Robotic foundation models pre-trained on human demonstration videos have shown promise, but a significant embodiment gap remains when the resulting policies are deployed on real robots.

By Beomjun Kim, Seong Hyeon Park, Seunghoon Sim, Seungjun Moon, Sanghyeok Lee, Jinwoo Shin

llms agents robotics fine-tuning benchmarks

arXiv AI

Jun 10

Uncertainty-Aware Motion Planning for Autonomous Driving in Mixed Traffic Environment

arXiv:2606. 09958v1 Announce Type: cross Abstract: In mixed-traffic environments where autonomous and human-driven vehicles may co-exist, motion planning for autonomous vehicles requires anticipating the future behaviors of surrounding human drivers.

By Ming Cheng, Hao Chen, Ziyi Yang, Ziluowen Luo, Senzhang Wang

agents reinforcement-learning robotics safety

arXiv AI

Jun 10

Co-GLANCE: Uncertainty-Aware Active Perception for Heterogeneous Robot Teaming

arXiv:2606. 09919v1 Announce Type: cross Abstract: Perceptual uncertainty is a central challenge for heterogeneous robot teams operating in unstructured outdoor environments, where no single viewpoint affords reliable scene understanding.

By Michal P. Podolinsky, Neel P. Bhatt, Pranay Samineni, Rohan Siva, Christian Ellis, Ufuk Topcu

llms computer-vision robotics efficiency multimodal

arXiv Machine Learning

Jun 10

Task Robustness via Re-Labelling Vision-Action Robot Data

arXiv:2606. 10918v1 Announce Type: cross Abstract: The recent trend in scaling models for robot learning has resulted in impressive policies that can perform various manipulation tasks and generalize to novel scenarios.

By Artur Kuramshin, \"Ozg\"ur Aslan, Cyrus Neary, Glen Berseth

llms robotics multimodal

arXiv AI

Jun 10

RoboGPT-R1: Enhancing Robot Task Planning with Reinforcement Learning

arXiv:2510. 14828v3 Announce Type: replace Abstract: Improving the reasoning capabilities of embodied agents is crucial for robots to complete complex human instructions in long-view manipulation tasks successfully.

By Jinrui Liu, Bingyan Nie, Boyu Li, Yaran Chen, Yuze Wang, Shunsen He, Haoran Li

llms agents reinforcement-learning robotics fine-tuning benchmarks

arXiv Machine Learning

Jun 10

Optimization-based Online Conformal Prediction for Multi-step Forecasting

arXiv:2508. 13362v2 Announce Type: replace Abstract: Conformal prediction (CP) is well-suited for uncertainty quantification in time series forecasting due to its distribution-free coverage guarantees.

By Ruipu Li, Daniel Menacho, Alexander Rodr\'iguez

agents robotics benchmarks

arXiv AI

Jun 10

BadRobot: Jailbreaking Embodied LLM Agents in the Physical World

arXiv:2407. 20242v5 Announce Type: replace-cross Abstract: Embodied AI represents systems where AI is integrated into physical entities.

By Hangtao Zhang, Chenyu Zhu, Xianlong Wang, Ziqi Zhou, Changgan Yin, Minghui Li, Lulu Xue, Yichen Wang, Shengshan Hu, Aishan Liu, Peijin Guo, Leo Yu Zhang

llms agents robotics benchmarks safety

arXiv AI

Jun 10

Gaming AI-Assisted Peer Reviews Poses New Risks to the Scientific Community

arXiv:2606. 10159v1 Announce Type: cross Abstract: AI is increasingly used to support scientific peer review, from manuscript screening, reviewer assistance to editorial triage.

By Lin Li, Qi Zhang, Xander Davies, Jianing Qiu, Yarin Gal

llms robotics safety

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 10

Exploration of Foundation Model-Based Robots in Patient and Elderly Care

arXiv:2606. 10208v1 Announce Type: cross Abstract: Demand for older-adult and patient care is growing rapidly as populations age worldwide.

By Zhiwen Qiu, Wei Liu, Yuexing Hao

agents robotics multimodal safety

arXiv AI

Jun 10

Dynamics of Adversarial Attacks on Large Language Model-Based Search Engines

arXiv:2501. 00745v3 Announce Type: replace-cross Abstract: The increasing integration of Large Language Model (LLM) based search engines has transformed the landscape of information retrieval.

By Xiyang Hu

llms robotics safety

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