Abstract: This paper presents a survey of the existing literature on the topic of Obstacle Avoiding vehicle. The rapid advancement of robotics and autonomous systems has fueled the development of intelligent vehicles capable of navigating through complex environments. This abstract presents a comprehensive overview of an obstacle-avoiding vehicle, designed to autonomously detect and circumnavigate obstacles in real-time. The vehicle's design, implementation, and evaluation are outlined, highlighting its key components and operational principles.The vehicle's hardware architecture includes a set of sensors, such as ultrasonic, infrared, or lidar, strategically placed to perceive the surrounding environment. These sensors provide input data for the obstacle detection and avoidance algorithms. The system employs sophisticated algorithms, such as computer vision techniques or machine learning models, to process sensor data and identify obstacles accurately.To ensure safe and efficient navigation, the vehicle incorporates an intelligent control system that generates appropriate motion commands based on obstacle detection. The control system leverages algorithms like path planning and decision-making techniques to determine the optimal trajectory, considering factors such as obstacle proximity, vehicle dynamics, and environmental constraints.Factors such as obstacle proximity, vehicle dynamics, and environmental constraints.The results of the evaluation demonstrate the successful implementation of the obstacle-avoiding vehicle, showcasing its capability to detect obstacles in real-lifeThe results of the evaluation demonstrate the successful implementation of the obstacle-avoiding vehicle, showcasing its capability to detect obstacles in real-time and maneuver around them effectively. The vehicle's performance exceeds predefined benchmarks, indicating its potential for various applications, such as indoor navigation, warehouse automation, or autonomous transportation.

| DOI: 10.17148/IARJSET.2023.10692