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At the intersection of perception, spatial reasoning, and decision-making, our research goal is to endow mobile robots with human-level autonomy. This vision drives us to develop algorithms and systems enabling robots to efficiently and robustly:
- Perceive and interpret various sensory inputs such as images, point clouds, and proprioceptive data.
- Integrate neural and symbolic representations of spatial common sense and semantic knowledge.
- Reason and plan 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.
- This GitHub organization provides source code for publications and teaching materials.
