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 in, interact with, and adapt within unstructured and dynamic environments.
About open-source.
SAIR Lab is leading PyPose, an open-source Python library for differentiable robotics on manifolds.
This GitHub organization provides source code for research and publications.
Teaching materials are available at GitHub organization sairclass.
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