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1,589 papers
The design, integration, and field deployment of an AI-assisted collaborative inspection cell at the Silverline kitchen-appliance factory is presented, developed within the AI-PRISM project.
WSM-Aware HRI is proposed, an IoT-enhanced modular framework that unifies diverse HRI breakdowns as World-State Mismatches (WSMs) between a human's instruction-implied assumptions and a robot's grounded world model built from multimodal perception and digital augmentation.
This v2 revision reports measured results on the completed implementation of DroneShield-AI, a unified open framework integrating six processing layers: RF signal classification, acoustic motor-signature detection, YOLOv8-based visual detection, evidence-weighted sensor fusion, a Behavioral Intent Classification Engine...
Experiments show that COVER improves the coverage-conflict trade-off, making CM-EVS a sparse, compact, and auditable RGB-D-pose resource for geometry-consistent panoramic 3D learning.
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ProcVLM is presented, a progress-aware vision-language model that learns procedure-grounded progress as a dense reward signal for manipulation and improves embodied procedural reasoning and yields more discriminative trajectory-internal progress estimates than representative baselines.
Pose-VLA is proposed, a decoupled paradigm that separates VLA training into a pre-training phase for extracting universal 3D spatial priors in a unified camera-centric space, and a post-training phase for efficient embodiment alignment within robot-specific action space.
Coral reefs are on the brink of collapse, with climate change, ocean acidification, and pollution leading to a projected 70-90% loss of coral species within the next decade. Reef restoration is crucial, but its success hinges on introducing automation to upscale efforts. In this work, we present a highly configurable A...
This study explores the application of RL in the context of SLAM by enabling the agent to iteratively interact with and receive feedback from its environment, which facilitates the acquisition of navigation and mapping skills, thereby enhancing the robot's decision-making capabilities.
The results distinguish cross-sensor consistency, multimodal fusion, and generalization to new action orders as separate questions as separate questions in evaluating multimodal physical representations.
Fast LeWorldModel (Fast-LeWM), a fast latent world model that replaces repeated local rollout with action-prefix prediction, improves average success over LeWM while substantially reducing planning time, achieving lower open-loop latent loss whose growth becomes significantly slower as the rollout horizon increases.
Long-horizon, sparse-reward tasks pose a fundamental challenge for reinforcement learning, since single-step TD learning suffers from bootstrapping error accumulation across successive Bellman updates. Actor-critic methods with action chunking address this by operating over temporally extended actions, which reduce the...
A statistically principled hard expectation-maximization procedure is introduced, with a Kalman smoother in the hard E-step, to identify dynamical representations of disturbance whose latent evolution is uniformly contractive, which yields a composite adaptive tracking controller with predictive capability and provable...
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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