RiskWorld, a risk-aware world modeling framework for shared occupancy forecasting and selective trajectory replacement, is introduced and within-setting ablations show that RiskWorld achieves lower collision rates than the current-state rescoring baseline, while forecast reuse enables additional candidates to be evalua...
Rong-Xiang Zeng, Lin-Sen Cai, Jia-Fu Zhang et al.· 0 citations
Automating biological research requires general-purpose, reproducible robot systems that allow individual wet-lab researchers to delegate robot tasks without performing teleoperation or neural-network training. Vision-language-action policies have been proposed for general-purpose arms, but can lose performance when th...
Yuna Oikawa, Kei Endo, Takanori Uzawa et al.· 0 citations
This work introduces Adaptive Agents via Latent Topologies (AALT), which requests demonstrations that maximize expected gains in start-goal connectivity and shows that this objective is formally tied to information gain about task reachability.
M. Jacobson, A. H. Qureshi, Ye-Xiang Xue· 0 citations
This work studies how much closed-loop driving competence a compact multimodal policy can acquire from offline demonstrations in the CARLA simulator, and reports offline metrics and distinguish measured results from qualitative closed-loop observations.
Jordy Kieto· 1 citation
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Under matched protocols on LIBERO and CALVIN, MPCoT improves long-horizon performance and support latent deliberation as a means of improving execution while preserving the action interface and generating no reasoning tokens.
Thanks to the latest advances in learning and robotics, domestic robots are beginning to enter homes, aiming to execute household chores autonomously. However, robots still struggle to perform autonomous manipulation tasks in open-ended environments. In this context, this paper presents a method that enables a robot to...
Mathilde Kappel, Mahdi Khoramshahi, Louis Annabi et al.· 0 citations
Recent advances in real-time interactive text-driven motion generation have enabled humanoids to perform diverse behaviors. However, kinematics-only generators often exhibit physical hallucinations, producing motion trajectories that are physically infeasible to track with a downstream motion tracking controller or uns...
Hanbyel Cho, Sang-Hun Kim, Jeonguk Kang et al.· 0 citations
Vision-language-action (VLA) models, world-action models (WAMs), and offline reinforcement learning methods are rapidly expanding the design space of embodied policies, yet turning these algorithms into reliable robot systems remains constrained by fragmented data formats, training stacks, evaluation protocols, inferen...
Yin-Hao Li, Wei-Xin Mao, Zi-Han Lan et al.· 2 citations
This framework surveys manipulation, navigation, locomotion, autonomous driving, and general embodied learning, tracing technical progressions, clarifying capability requirements, and examining datasets, benchmarks, and evaluation protocols.
Nan-Jie Yao, Hao Wang, Chong Cheng et al.· 0 citations
ProxiDex is presented, a dynamics-guided proximity policy framework that treats hand-object proximity as an interaction state for dexterous manipulation, and adaptively reweights proximity tokens across manipulation phases and uses dynamics-consistency supervision to guide policy inference, stabilizing action generatio...
Yu-Shan Bai, Bo-Yu Zheng, Zhi-Yang Mao et al.· 0 citations
UDAV, an Uncertainty-Driven Adaptive VLM Waypoint Planner for UAV-guided UGV navigation is presented, demonstrating that stochastic VLM predictions provide both a stronger nominal route and an actionable uncertainty signal for selectively mitigating large planning errors.
AssemblyGrid v1 is introduced, a reproducible benchmark for repeated multi-robot production that combines explicit process progression, decentralized observations, material transfer, temporary multi-robot coalitions, productive concurrency, and geometry-dependent feasibility within one task-level formulation.
Fouad Bahrpeyma, David Heik, Dirk Reichelt· 0 citations
Robots are getting smarter, but how can their hardware match that growth? New Microsoft Research findings show that moving AI inference beyond the robot can improve task success, boost efficiency, and support more advanced physical AI workloads. The post Offloaded inference for real-world physical AI robotics appeared first on Microsoft Research.
Gemini Robotics ER 2 helps robots reason, collaborate, and solve real-world tasks. It represents a step change in video understanding, tool orchestration, and multi-robot collaboration for robotic applications.
From feet to fingertips — we are teaching robots intelligent whole-body control, fine dexterity, and teamwork to complete a broad range of complex tasks.
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