Automating the Operation of a 3D-Printed Unmanned Ground Vehicle in Indoor Environments

Abstract

The United States Department of Defense anticipates unmanned systems will be integrated into most defense operations by 2030 to reduce risk to human life, enhance reliability, and ensure operation consistency and efficiency. However, current technology requires human operation for ethical decision-making, leaving an opportunity to automate some tasks to assist operators. Previously, a University of Virginia capstone team designed an unmanned ground vehicle (“the rover”) to aid intelligence, surveillance, and reconnaissance missions in adversarial environments. However, a lack of GPS connectivity indoors and system latency limited the rover's performance and created a lag in the operator's view compared to the rover's true position, occasionally causing the operator to inadvertently crash the rover into obstacles. The objectives of this project are to mitigate operational risks by equipping the rover with functionalities to autonomously avoid obstacles, map an unknown indoor space, and navigate itself back to a predetermined location (“base”). Obstacle avoidance is accomplished through an algorithm that stops the rover a safe distance away from a detected obstacle, but still allows the human operator to navigate the rover away from the obstacle prior to continuing the mission. Algorithms are implemented to perform Simultaneous Localization And Mapping and to determine best-route navigation to the base. Laser rangefinder data, an improved processor, and, potentially, visual odometry sensors are used to aid in the navigation algorithms. Testing has confirmed that the rover successfully stops in front of laser-detected obstacles, builds digital maps of an unknown indoor space, and can navigate back to a base, though the performance has room for improvement. It is anticipated that incorporating visual odometry can enhance the rover's mapping implementation and obstacle avoidance performance.