This project was build as a requirement for course CSE 571 Artificial Intelligence at Arizona State University. This system simulates a TurtleBot in Gazebo environment. It simulates a robot whose objective is to reach all destination nodes in the generated grid. The bot tries to find the most optimal plan.
- Install TurtleBot3.
- Clone this repository, extract content in the source folder.
- Navigate to src folder
- Run "python server.py" to run the server.
- Run the roscore command to enable movement.
- Run astar.py. This script tries to find a plan for the turtlebot. If it finds plans, it sends navigation commands to the turtlebot using pid controller.
- If a plan is generated, the turtle will start moving to the requirement location.
Please refer to this demo video
- Adding obstacles
- Simulating same problem in different types of environments (non-observable, partially observable, stochastic, non-stochastic)
The AAIR lab at ASU has various projects posted on their github page. Please check them out here