Comparison of Path Planning between Improved Informed and Uninformed Algorithms for Mobile Robot

Abstract

This work is concerned with the Path Planning Algorithms (PPA), which hold an important place in Robotics navigation. Navigation has become indispensable to most modern inventions. Mobile robots have to move to a relevant task point in order to achieve the tasks assigned to them. The actions, which are planned in a structure, may restrict the task duration and even in some situations, the mission tends to be accomplished. This paper aims to study and compare six commonly used informed and uninformed algorithms. Three different maps have been created with gradually increasing difficulty levels related to a number of obstacles in the tested maps. The paper provides a detailed comparison between the algorithms under investigation of several parameters such as: Total steps, straight steps, rotation steps, and search time. The promised results were obtained when the proposed algorithms were applied to a case study.

Faster than Dijkstra and A* Methods for the Mobile Robot Path Planning Problem Using Four Movement Directions: The Dhouib-Matrix-SPP-4

“…Based on the representation of the environment as a grid map, the modeling and simulation analyses are carried out under a DELL Laptop using an Intel® Core™ i7-1255U 1.7 GHz processor, 16 Go RAM, Windows 10 operating system and Python platform. The performance of the proposed DM-SPP-4 method is tested on three environments (Easy, Medium and Hard maps represented by a 41x41 grid model) and compared to six methods developed by [29]: Basic Dijkstra (B-Dijkstra), Modified Dijkstra (M-Dijkstra), A*, Modified A* (M-A*), Best First Search Algorithm (BFS), Breadth First Search (BRFS), Depth First Search (DFS).…”

Genetic algorithm for finding shortest path of mobile robot in various static environments

“…The Breadth-First Search (BFS) [7], Depth-First Search (DFS), Best-First Search, and Dijkstra algorithms [8] are the most popular classical methods for path planning, enabling identification of the shortest path between nodes in a graph and grid-based structures or known as single-source shortest path (SSSP) problem [9]. Greedy BFS [10] and A* algorithm [11], [12] are two heuristic, goal-oriented search algorithms that are faster than the aforementioned algorithm.…”