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Navigating a vehicle autonomously and safely in unknown surroundings to a desired destination is challenging due to lack of initial information about stationary and moving objects along the path. This thesis proposes a navigation system that avoids static and dynamic obstacles using weighted real-time sensor feedback. The effectiveness of the system is demonstrated by implementing it on a robot. A 16-beam solid-state LiDAR sensor is used to detect obstacles to control a differential drive mobile robot. The sensor measurements are weighted and integrated into the Pure Pursuit path following algorithm to avoid obstacles in a natural smooth movement. The primary purpose of this thesis is to integrate all the sensors and processing units to create an appropriate reaction of the robot while it progresses toward the destination. The Algorithm proposed in this work guided the robot safely and fluently from start to end position while avoiding obstacles along the path.
Advisor: | Hamano, Fumio |
Commitee: | Hossein, Jula, Khoo, I-Hung |
School: | California State University, Long Beach |
Department: | Electrical Engineering |
School Location: | United States -- California |
Source: | MAI 58/03M(E), Masters Abstracts International |
Source Type: | DISSERTATION |
Subjects: | Robotics |
Keywords: | Control and automation, Differential drive robot, Navigation, Obstacle avoidance, Sensor fusion, Weighted feedback |
Publication Number: | 10977871 |
ISBN: | 978-0-438-71865-4 |