GTSAM is a library of C++ classes that implement smoothing and mapping (SAM) in robotics and vision, using factor graphs and Bayes networks as the underlying computing paradigm rather than sparse matrices.
Evaluating and reproducing real-world robot manipulation policies (e.g., RT-1, RT-1-X, Octo) in simulation under common setups (e.g., Google Robot, WidowX+Bridge) (CoRL 2024)
Massively parallel rigidbody physics simulation on accelerator hardware.
Code examples for Robotics, Vision & Control 3rd edition in Python
[CoRL 2026] EgoWAM: World Action Models Beyond Pixels with In-the-Wild Egocentric Human Data
Notebook-based book "Introduction to Robotics and Perception" by Frank Dellaert and Seth Hutchinson