[CVPR 2023 Best Paper Award] Planning-oriented Autonomous Driving
- autonomous-driving
- end-to-end-autonomous-driving
- motion-prediction
- multi-object-tracking
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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.
- estimation
- perception
- robotics
- sensorfusion
pySLAM is a hybrid Python/C++ Visual SLAM pipeline supporting monocular, stereo, and RGB-D cameras. It provides a broad set of modern local and global feature extractors, multiple loop-closure strategies, a volumetric reconstruction module, integrated depth-prediction models, and semantic segmentation capabilities for enhanced scene understanding.
- 3d-reconstruction
- depth-prediction
- feature-matching
- global-features
Hybrid A* Path Planner for the KTH Research Concept Vehicle
- motion-planning
- planning-algorithms
- robotics
Gibson Environments: Real-World Perception for Embodied Agents
- computer-vision
- robotics
- simulator
- sim2real
Point cloud registration pipeline for robot localization and 3D perception
- robot-localization
- localization
- robotics
- mapping
Real-Time 3D Semantic Reconstruction from 2D data
- semantic-segmentation
- volumetric-reconstruction
- 3d-reconstruction
- robotics
Modular autonomous driving platform running on the CARLA simulator and real-world vehicles.
- autonomous-vehicles
- autonomous-driving
- carla
- perception
Independent reproduction of SuperMimic (arXiv:2610.28480) on mjlab/MuJoCo Warp, written from the paper before the official release. For the authors' code see HybridRobotics/supermimic. Kept as a record: experiment log, full BONES-SEED results, checkpoint.
- humanoid
- mjlab
- motion-tracking
- mujoco
HALO: Perceptive Humanoid Motion from Simulation
Artificial Intelligence for Kinematics, Dynamics, and Optimization
CARLA-based cooperative perception system integrating YOLO26n, V2I communication, sensor fusion, TTC risk assessment, and automated braking.