Path discovering in maze area using mobile robot

Abstract

Robotic maze pathfinding problems deal with detecting the correct route from the start point to the end-point in a virtual maze environment consisting of walls. Automated robot mobility is a significant feature, which enables a mobile robot to traverse a maze independently, from one position to another, without human intervention. There is a myriad of autonomous industrial mobile robot applications, including the transportation of goods and parts, domestic cleaning, indoor security surveillance, airport baggage couriering, and a plethora of other applications to traverse dangerous locations. This paper proposes a pathfinding mobile robot in a virtual maze based on a combination of a simplified left-hand algorithm and a line-following control algorithm. The mobile robot works in any maze to determine a route from the initial starting point to the end-point. The approach outlined in this paper uses a left-hand algorithm to solve the maze problem and a line-follower control algorithm to enable the robot to move in a straight line through the virtual maze. The algorithm used is less complicated and prevents the robot from falling into infinity loops compared to the traditional wall-follower algorithm.

Ultrasonic sensor decision-making algorithm for mobile robot motion in maze environment

“…Rudzuan et al [15] introduced an experimental attempt to minimize errors that occurred in following the path taken by a mobile robot redirects it to a stable target point. Mohammed et al [16] proposed the integration of a line-tracking control algorithm and a simplified left-handed algorithm for a moving robot in a virtual maze. Research by Zhmud et al [17] focused on the HC-SR04 ultrasound rangefinder with the STM32VLDISCOVERY evaluation board.…”

Simulation of autonomous navigation of turtlebot robot system based on robot operating system

“…The majority of the costs related to manual material handling are due to labor costs; however, the use of autonomous robots is becoming increasingly common in industrial applications. By utilizing these autonomous robot vehicles, the plant can save up to 30% on material handling costs [9], [10]. With minimal assistance, these self-driving robots possess the ability to traverse their surroundings autonomously in hazardous areas for workers.…”

Multi-layer perceptron neural network mobile robot navigator in unknown environment

“…Improving the robot's movement in avoiding obstacles was done [28] using neuro-fuzzy in this work led to enhance response and decrease time response. Discovering the path in any maze map using MATLAB was presented in [29], where the robot follows the walls to find the correct path between the start point and end point. The algorithm shows good results but it has suffered from time consumption.…”