IMPORTANT NOTE:

This repository provides an implementation of SPOT algorithm in gym pybullet environment.

$ conda env create -f environment.yml
$ conda activate drones
$ pip3 install --upgrade pip
$ git clone https://github.com/Astik-2002/SPOT-Spatio-Temporal-Obstacle-free-Trajectory-Planning-for-UAVs-in-unknown-dynamic-environments
$ cd SPOT-Spatio-Temporal-Obstacle-free-Trajectory-Planning-for-UAVs-in-unknown-dynamic-environments/
$ pip3 install -e .

Examples

The core algorithm is implemented in rrt_path_finder ros2 package in [SPOT-Spatio-Temporal-Obstacle-free-Trajectory-Planning-for-UAVs-in-unknown-dynamic-environments/ros2/] Directory super_planner provides the implementation of SUPER (https://github.com/hku-mars/SUPER) in the gym pybullet environment. For running the planner, run the command

$ ros2 run ros2_gym_pybullet_drones benchmark_toast