Modeling and Design of an Autonomous Amphibious Vehicle with Obstacle Avoidance for Surveillance Applications

The autonomous vehicle system is built on the autopilot technique, allowing the vehicle to operate without human intervention. Equipped with sensors and actuators, the vehicle can perceive its surroundings and navigate autonomously. This promises to significantly reduce driving fatalities by replacing fallible human drivers with advanced computerized systems. With little responsibility on the driver’s part, these vehicles can travel anywhere, much like traditional cars, without requiring human assistance. The intricate system relies on sensors, actuators and complex algorithms, with each component responsible for various functions and real-time control. Such systems can revolutionize surveillance applications by providing a versatile and reliable means of transportation for monitoring operations in various terrains and environ ments. To modernize the autonomous vehicle model and make it more flexible and safe, a new system has been proposed in this paper that uses ultrasonic sensors and motor drivers for visualisation of surrounding and accordingly planning of their motion. It generally detects the obstacle by ultrasonic waves which when reflected back tell about the distance through the fed program logic. On that basis, the vehicle movement is controlled and managed in the real-time environment. The proposed autonomous vehicle system is designed to operate an amphibious vehicle, which can travel on both land and water, serving as a versatile means of transportation with obstacle avoidance regardless need of cameras on the vehicle for object detection and classification and then movement controlling. The experimental results indicate the effectiveness of the proposed system where the machine-learning algorithms are not required for effective controlling and movement of the vehicle. However, the need of efficient sensors and actuators are required for better controlling and handling for the proposed system to work efficiently in real-time environments.