Welcome to the Applied Planning, Learning, and Optimization (APOLLO) Lab at Yale! Our lab focuses on pushing the boundaries of robotics by exploring innovative approaches in motion generation, manipulation learning, and the integration of continuous and discrete reasoning. We combine advanced planning, optimization, and learning methods to enable robots to navigate and interact more effectively in dynamic environments. Our research spans areas like automatic differentiation for optimization, improving mixed-integer programming solvers, and unifying spatial computing concepts such as geometric algebra. These efforts are aimed at solving real-world challenges in fields like autonomous systems, disaster recovery, and healthcare.

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