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1,589 papers
This work argues that their continual coordination under competing demands constitutes an important and underexplored target for modern robot learning and proposes the ethological behavioral substrate as a conceptual lens for studying this form of competence in artificial agents.
VPTwin is proposed, a Real-Sim-Real video prediction framework that anchors real-world future prediction using real-synchronized simulation twins and establishes a predictive planning loop using VPTwin to visually verify VLM-proposed actions and guide reliable real-world execution.
A high-performing teacher is built that makes navigation evidence selection explicit and compressible, and a compact student is trained by transferring both where to attend and what to do, then further match action distributions during fine-tuning.
CAPEX, an experience-conditioned demonstration collection framework that uses execution experience from previous attempts to adapt how frequently the foundation model must observe, reason, and replan, is introduced and suggests that foundation models can serve as scalable sources of reusable robot experience.
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It is found that, given task-specific natural-language guidance, VLMs can estimate actuator-response relationships, resolve ambiguous observations through intervention, and actively create informative visual feedback when signals are sparse, suggesting that pretrained multimodal models can serve as important decision-m...
The results show that inference-time parameter variation is a reliable, training-free source of path diversity, and that H-Graph hybridization reliably converts this diversity into shorter, higher quality trajectories.
RoboFoundry is proposed, the first embodied agentic framework that formulates this process of system-as-policy evolution across foundation models as Self-Evolving System-as-Policy, highlighting its potential for fully autonomous embodied agents.
Ultrasound (US) acquisition depends on the operator's ability to interpret anatomy and anticipate how the view will change with probe motion. Many robotic US navigation methods select actions without explicitly predicting these anatomical changes. We propose SonoGraph-WM, an action- and goal-conditioned world model for...
RECAST is a robot navigation framework that combines the reasoning of a VLM with the spatial grounding of vision foundation models to build an Actionable Cost map and improves success over the strongest prior method.
Robotic manipulation is inherently history-dependent, yet most pretrained robotic policies condition on only the current observation or a short temporal window. Equipping such policies with long-term memory remains challenging: existing approaches either feed the backbone multi-frame observation windows, which substant...
RE-0, a recursively verified policy improvement framework, which improves both teacher-assisted execution and the standalone student, and generalizes to novel robots and scenes, and RE-OPD, which turns verified interventions into supervision for on-policy distillation.
Vision-and-language navigation increasingly relies on general-purpose semantic planners, yet translating correct high-level intent into reliable physical execution remains difficult in spatially constrained transitions. Reaching a staircase, doorway, or narrow passage does not ensure traversal; the agent must identify...
A Blog post by Ai2 on Hugging Face
A new system identifies and corrects unreliable object descriptions stored in a robot’s memory, improving the robot’s ability to interact with its environment.
Discover Gemini 4 Argon for robotics: leading the ERQA benchmark with physical reasoning, zero-shot control, Real2Sim, and agentic workflows.
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.
A Blog post by Amazon on Hugging Face
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