Robotics Domain
Robotics research currently focuses on enhancing robot autonomy, safety, and dexterity, particularly in unstructured environments. Key areas include developing robust control algorithms (like Model Predictive Control and reinforcement learning), improving perception through advanced sensor fusion and generative models, and creating more efficient and adaptable robot designs. These advancements are driving progress in diverse applications such as agriculture, healthcare, and manufacturing, ultimately aiming to create more capable and reliable robots for a wider range of tasks.
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Papers
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Reward Training Wheels: Adaptive Auxiliary Rewards for Robotics Reinforcement Learning
Safety Aware Task Planning via Large Language Models in Robotics
Reinforcement Learning for Robust Athletic Intelligence: Lessons from the 2nd 'AI Olympics with RealAIGym' Competition
A Unified Framework for Real-Time Failure Handling in Robotics Using Vision-Language Models, Reactive Planner and Behavior Trees
March 15, 2025
March 13, 2025
March 11, 2025