Development of Obstacle Navigation in Robots Using the Linear Regression Method

Navigation systems play a crucial role in robotic devices, enabling autonomous movement by determining position, direction, and efficiently guiding the robot from one location to another. These systems are vital in applications such as gas-sensing robots, which are used to map and localize gas distribution sources, including dust pollution. Advanced navigation systems significantly reduce sensing time and enhance mapping accuracy, making them indispensable in modern robotics. This research focuses on developing a navigation system based on Linear Regression Method and odometry sensors, achieving an accuracy of approximately 93.97%. These advancements enable robots to perform tasks more efficiently in hazardous or inaccessible environments, such as disaster sites or contaminated areas, while also contributing to safety, convenience, and quality of life in everyday contexts, such as home cleaning and gardening. Additionally, the research opens new opportunities in the robotics and technology sectors. The findings provide valuable insights for optimizing autonomous navigation systems and offer a foundation for future advancements in robotic technologies.