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At the intersection of perception, spatial reasoning, and decision-making, we are committed to advancing mobile robots toward human-level autonomy by developing algorithms and systems that can efficiently and robustly:
- Perceive and interpret various sensory inputs such as images, point clouds, and proprioceptive data.
- Integrate neural and symbolic memory representations to capture spatial common sense and semantic knowledge.
- Reason, plan, and act in real time to navigate, interact, and adapt within unstructured and dynamic environments.
- SAIR Lab is leading PyPose, an open-source Python library for differentiable robotics on manifolds.
- This GitHub organization provides source code for publications and teaching materials.
