Advancements in Obstacle Detection for Arduino Systems
Keywords:
Arduino, Autonomous navigation, Delivery drones, Warehouse automation, LIDAR sensorAbstract
The development of autonomous vehicles has been a significant area of research in the fields of robotics and artificial intelligence. These vehicles, capable of navigating their environment without human intervention, have applications in various industries, such as transportation, warehouse automation, and robotics competitions. The goal of an obstacle-avoiding vehicle is to enable a machine to detect and avoid obstacles, ensuring smooth navigation in unpredictable environments. Arduino, an open-source electronics platform, is often used in research and prototype development due to its simplicity, affordability, and flexibility. By combining Arduino with various sensors and actuators, researchers can create effective systems for autonomous navigation. In recent decades, autonomous vehicles have evolved from basic robotic systems to more advanced, self-driving cars that can navigate complex environments. The initial focus was on creating basic robots capable of performing tasks like following a line or avoiding obstacles. With advances in sensor technology, such as ultrasonic, infrared, and LIDAR sensors, these vehicles have become more adept at sensing their surroundings and making real-time decisions. One of the core challenges for autonomous vehicles is the ability to avoid obstacles while navigating. This capability is crucial not only for robotics but also for practical applications such as delivery drones, automated warehouse robots, and self-driving cars. Obstacle detection and avoidance help prevent accidents, improve efficiency, and increase the reliability of autonomous systems.
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