casADi

pinocchio

A fast and flexible implementation of Rigid Body Dynamics algorithms and their analytical derivatives

EGO-Planner

EGO-Planner is an ESDF-free gradient-based local planner designed for quadrotor navigation. It significantly reduces computation time compared to state-of-the-art methods by avoiding the computationally expensive Euclidean Signed Distance Field (ESDF) construction, enabling real-time performance with total planning times around 1ms. ## Key Features - **ESDF-Free Planning** — Eliminates the need to compute Euclidean Signed Distance Fields, drastically reducing computational overhead. - **Lightweight Gradient-Based Optimization** — Uses a gradient-based approach for efficient local trajectory generation. - **GPU/CPU Versatility** — Offers both GPU and CPU versions of its local sensing module for depth image generation or pointcloud processing. - **Fast Computation** — Achieves planning times of approximately 1ms, suitable for real-time drone control. - **Simulation-Ready** — Includes a lightweight quadrotor simulator and supports integration with sensors like Intel RealSense for hardware testing. ## Philosophy EGO-Planner prioritizes computational efficiency and real-time performance by removing the ESDF construction bottleneck, making advanced local planning accessible for resource-constrained aerial robotics applications.

ompl

The Open Motion Planning Library (OMPL)

path_planner

Hybrid A* Path Planner for the KTH Research Concept Vehicle