An Open-source Strong Baseline for SE(3) Planning in Autonomous Drone Racing
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Updated
Aug 23, 2021 - C++
An Open-source Strong Baseline for SE(3) Planning in Autonomous Drone Racing
Implementation of SE3-Transformers for Equivariant Self-Attention, in Pytorch. This specific repository is geared towards integration with eventual Alphafold2 replication.
A complete, hardware-ready Python package for Koopman-based Linear Model Predictive Control (LMPC), delivering real-time trajectory tracking for quadrotors using analytical Koopman lifting (no training data required)
Robot Motion Estimate: Tools, Variables, and Factors for SLAM in robotics; also see Caesar.jl.
Implementation of Lie Transformer, Equivariant Self-Attention, in Pytorch
Lie groups and algebra with some quaternions
SE3 interpolation and Quat+R^3 interpolation are implemented.
A C++ Eigen-based maths library for robotics applications, including SO(3) and SE(3) transformations, screw motions, robot kinematics, and control laws. All the codes are successfully tested in ROS 2 humble.
Numerically stable implementation of batched SE(3) exponential and logarithmic maps
Benchmarking library for SE(3) Manifold Optimization: Geometric Dual Quaternions (GeoDQ), ESKF, and UKF-M implementations for Robotics & Navigation
Lightweight C++ header-only template library for translation, rotation and homogeneous transformation. Requires C++17 or Later. No dependencies with other libraries and stl.
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