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Found 2 papers, 1 papers with code
Adaptive Reinforcement Learning for Robot Control
Deep reinforcement learning (DRL) has shown remarkable success in simulation domains, yet its application in designing robot controllers remains limited, due to its single-task orientation and insufficient adaptability to environmental changes.
AirCapRL: Autonomous Aerial Human Motion Capture using Deep Reinforcement Learning
We focus on vision-based MoCap, where the objective is to estimate the trajectory of body pose and shape of a single moving person using multiple micro aerial vehicles.
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