REAL-TIME OBSTACLE AVOIDANCE AND WAYPOINT NAVIGATION OF AN UNMANNED GROUND VEHICLE

Real-time obstacle avoidance and navigation are key fields of research in the area of autonomous vehicles. The primary requirements of autonomy are to detect or sense changes and react to them without human intervention in a safe and efficient manner The objective of this research is to develop autonomous waypoint navigation and obstacle avoidance capabilities for an unmanned ground vehicle (UGV). This research consists of developing and implementing an environment mapping system capable of detecting and localizing potential obstacles using real-time sensor data. The real-time obstacle mapping system developed in this work automatically generates the Probabilistic Threat Exposure Map (PTEM). The PTEM construction algorithm successfully constructs a probabilistic obstacle map both in simulation and real-time. Autonomous waypoint navigation is also achieved for both simulation and real-time platforms. These activities are a part of a larger effort to establish a theoretical foundation and real-time implementation of autonomous and cooperative multi-UxV guidance solutions in adversarial environments.