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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…
Theia: A Robot Vision Foundation Model that Simultaneously Distills Off-the-Shelf VFMs such as CLIP, DINOv2, and ViT
Visual understanding is the abstracting of high-dimensional visual signals like…
Google DeepMind Researchers Present Mobility VLA: Multimodal Instruction Navigation with Long-Context VLMs and Topological Graphs
Technological advancements in sensors, AI, and processing power have propelled…
Hyperion: A Novel, Modular, Distributed, High-Performance Optimization Framework Targeting both Discrete and Continuous-Time SLAM Applications
In robotics, understanding the position and movement of a sensor…
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