This is a highly-optimized implementation for minimum jerk/snap trajectories with exact gradient w.r.t. time allocation and waypoints. All involved computations enjoy linear time and space complexity. It is based on completely analytical results of our paper. Only two header files are all you need to use our module as a super efficient differentiable black box.


Generating Large-Scale Trajectories with Polynomial Double Descriptions

EGO-Swarm is a decentralized and asynchronous systematic solution for multi-robot autonomous navigation in unknown obstacle-rich scenes using merely onboard resources.


EGO-Swarm: A Fully Autonomous and Decentralized Quadrotor Swarm System in Cluttered Environments

TGK-Planner is a hierarchical trajectory planner for multirotors with a sampling-based kinodynamic front-end and an optimization back-end. It can serve as a global kinodynamic planner to find asymptotically optimal trajectories or as a local kinodynamic planner for quick replans.


TGK-Planner: An Efficient Topology Guided Kinodynamic Planner for Autonomous Quadrotors

A lightweight gradient-based local planner without ESDF construction, which significantly reduces computation time compared to some state-of-the-art methods. The total planning time is around 1ms for a trajectory with normal scale.


EGO-Planner: An ESDF-free Gradient-based Local Planner for Quadrotors

A library for generating large-scale piecewise polynomial trajectories for aggressive autonomous flights, with highlights on its superior computational efficiency and simultaneous spatial-temporal optimality. Besides, an extremely fast feasibility checker is designed for various kinds of constraints. Our method is capable of computing a spatial-temporal optimal trajectory with 60 pieces within 5ms, i.e., 200Hz.


Alternating Minimization Based Trajectory Generation for Quadrotor Aggressive Flight

Detailed Proofs of Alternating Minimization Based Trajectory Generation for Quadrotor Aggressive Flight

A complete and robust system containing all components for UAV aggressive flight in complex environments. Our system can capture users’ intention of a flight mission, convert an arbitrarily jerky teaching trajectory to a guaranteed smooth and safe repeating trajectory, and generate safe local re-plans to avoid unmapped or moving obstacles on the flight.

paper: Teach-Repeat-Replan: A Complete and Robust System for Aggressive Flight in Complex Environments

A quadrotor trajectory generator which combines kinodynamic path search and gradient-based trajectory optimization for fast autonomous flight.

paper: Robust and Efficient Quadrotor Trajectory Generation for Fast Autonomous Flight

A framework for online generating safe and dynamically feasible trajectories directly on the point clouds.

paper: Flying on Point Clouds: Online Trajectory Generation and Autonomous Navigation for Quadrotor in Cluttered Environments

An online UAV planning framework used to generate safe, dynamically feasible trajectories in unknown environments

paper: Online Safe Trajectory Generation For Quadrotors Using Fast Marching Method and Bernstein Basis Polynomial