Autonomous Maneuver through Square Targets

Students: Shakeeb Ahmad, Greg Brunson

The main idea behind the project is to develop a fully autonomous system, free of external sensings like motion capture and GPS. At the same time, it should be capable of sensing its environment for various tasks. NVIDIA Jetson TK1 is used as the main processor on-board while a forward-facing ZED stereo camera is used to get visual odometry and to detect objects in the environment. The test prototype is then used to implement autonomous navigation through a set of square targets. The stereo camera is hence used to detect the square targets and their center points and finally, a path is planned through the center points. The algorithm is implemented in C++ using the Robot Operating System (ROS) framework.

[1] Ahmad, Shakeeb, “High-Performance Testbed for Vision-Aided Autonomous Navigation for Quadrotor UAVs in Cluttered Environments”, The University of New Mexico (Digital Repository), 2018