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Researchers at Physical Intelligence Introduce π-0.5: A New AI Framework for Real-Time Adaptive Intelligence in Physical Systems
Designing intelligent systems that function reliably in dynamic physical environments…
Sensor-Invariant Tactile Representation for Zero-Shot Transfer Across Vision-Based Tactile Sensors
Tactile sensing is a crucial modality for intelligent systems to…
π0 Released and Open Sourced: A General-Purpose Robotic Foundation Model that could be Fine-Tuned to a Diverse Range of Tasks
Robots are usually unsuitable for altering different tasks and environments.…
Researchers from Stanford and Cornell Introduce APRICOT: A Novel AI Approach that Merges LLM-based Bayesian Active Preference Learning with Constraint-Aware Task Planning
In the rapidly evolving field of household robotics, a significant…
Google DeepMind Researchers Propose RT-Affordance: A Hierarchical Method that Uses Affordances as an Intermediate Representation for Policies
In recent years, there has been significant development in the…
Latent Action Pretraining for General Action models (LAPA): An Unsupervised Method for Pretraining Vision-Language-Action (VLA) Models without Ground-Truth Robot Action Labels
Vision-Language-Action Models (VLA) for robotics are trained by combining large…
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