Grid Based Realistic Optimal Path Planning

Abstract

The indoor mobile robot trajectory planning algorithm is widely used across the real world mobile robots applications. There are many types of algorithm that are based on the grid based path planning. Path Planning Algorithms is the major module for deciding the trajectory to move mobile robot to reach the target. The robot is equipped with multiple on body sensors that helps it to calculate the path and shortest distance needed for navigating. Although the moving mobile robot is unaware of the environment components and objects within application boundary, the incorporated sensors explores the in-path objects so as to explore more safest and feasible path. This research paper mainly focused on the development of novel grid based path finding algorithms which overcomes the traditional indoor mobile robot path finding algorithm shortcoming and making more realistic end solution for a variety of robotic and game development application. The proposed novel "Realistic Optimal Path Planning Algorithm” (ROPPA), utilize cell pruning techniques to improve the explored path length.  Also this method takes care of future non-collision of mobile robot with in-path obstacle, while utilizing the uniquely designed set of rules. This method improves the overall computation time and path cost requires by 25% compared to traditional path planning algorithm.