Robot Morphology
Robot morphology research focuses on designing and optimizing robot bodies for improved performance in various tasks and environments. Current efforts concentrate on developing universal control policies applicable across diverse robot morphologies, often leveraging graph neural networks, transformers, and reinforcement learning to address the challenges of high-dimensional control and efficient adaptation to unseen robots. This research is significant because it enables more robust, adaptable, and efficient robots, impacting fields ranging from industrial automation and search-and-rescue to the fundamental understanding of embodied intelligence.
Papers
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