Motion of Mobile Robots in Environments with Dynamic Obstacles and Arbitrary Directions

Abstract

This paper presents an improved study on the motion of mobile robots with dynamic obstacle environments and arbitrary directions. This study focuses on incorporating the concept of inertia into the movement of obstacles to enhance the capabilities of mobile robots in complex environments. Unlike random movements, the obstacles in this study possess inertia, which constrains their motion in predictable patterns. This inertia can be learned or predicted by the robot, enabling it to better anticipate the obstacle positions. This research employs a grid-based simulation environment with systematically moving obstacles. By considering inertia, the robot gains the ability to understand and leverage the predictable aspects of obstacle motion, resulting in improved navigation performance. The robot can predict obstacle trajectories more effectively, reducing the likelihood of collisions and increasing overall efficiency by using the velocity obstacle algorithm. By incorporating inertia into the movement of obstacles, the robot gains valuable insights that enable it to plan its movements more intelligently. Incorporating inertia as a factor in obstacle motion contributes to a more systematic and predictable environment, allowing the robot to make informed decisions based on the anticipated positions of both fixed and moving obstacles. This research opens up possibilities for further advancements in mobile robot navigation in complex environments and dynamic scenarios.