Time
May 2017 – July 2017
Summary
During this project, I work with Prof. Dimitra Panagou and Ph.D Kunal Garg to develop a simulation environment for multi-agent trajectory planning. This simulation environment can be generalized to different maps including buildings, trees, cars, people, etc., with different aircraft like quadrotors, airplanes, etc.
I use ROS (robotics operating system), gazebo, Matlab, c++ to interact with each other and create a visualized UI in gazebo to simulate the trajectory of multi agents. In detail, I use c++ to receive position of the quadrotors from ROS and send it to Matlab. Since Matlab is efficient in calculation, I use Matlab to calculate the speed of quadrotors based on the received postion using the multi-agent trajectory planning algorithm. Then Matlab sends speed back to c++ and c++ eventually sends speed back to ROS. This working system can be applied to many Multi-agent Trajectory Planning algorithms as long as they calculate the speed based on positions.
What’s more, to make the simulation environment more realistic, I add many different obstacles in the gazebo simulation environment like buildings, trees, cars and so on. The position and dimension of these obstacles can be adjusted easily by only changing a few variables. Moreover, with the help of SketchUp, I import many online models to gazebo which simulates a much more realistic world. In the meantime, in addition to the quadrotors models, I also create a Boeing-747 airplane model for those algorithms designed for airplanes.
Architecture
Demo Video
Quadrotors
Airplanes
Document
Click here to see detailed project document.
Related Code
You can contact me if you want to see the actual implementation. I can add you to the private Github repo.
Yucheng Yin 