ARTIFICIALLY INTELLIGENT MAZE SOLVER ROBOT

International Journal of Mechanical Engineering and Robotics Research, 2017

Technologies (Basel), 2023

Advances in the development of collision-free path planning algorithms are the main need not only to solve mazes with robotic systems, but also for their use in modern product transportation or green logistics systems and planning merchandise deliveries inside or outside a factory. This challenge increases as the complexity of the task in its structure also increases. This paper deals with the development of a novel methodology for solving mazes with a mobile robot, using image processing techniques and graph theory. The novelty is that the mobile robot can find the shortest path from a start-point to the end-point into irregular mazes with abundant irregular obstacles, a situation that is not far from reality. Maze information is acquired from an image and depending on the size of the mobile robot, a grid of nodes with the same dimensions of the maze is built. Another contribution of this paper is that the size of the maze can be scaled from 1 m × 1 m to 66 m × 66 m, maintaining the essence of the proposed collision-free path planning methodology. Afterwards, graph theory is used to find the shortest path within the grid of reduced nodes due to the elimination of those nodes absorbed by the irregular obstacles. To avoid the mobile robot to travel through those nodes very close to obstacles and borders, resulting in a collision, each image of the obstacle and border is dilated taking into account the size of the mobile robot. The methodology was validated with two case studies with a mobile robot in different mazes. We emphasize that the maze solution is found in a single computational step, from the maze image as input until the generation of the Path vector. Experimental results show the usefulness of the proposed methodology, which can be used in applications such as intelligent traffic control, military, agriculture and so on.

International Journal of Computer Applications, 2012

Autonomous navigation is an important feature that allows a mobile robot to independently move from a point to another without an intervention from a human operator. Autonomous navigation within an unknown area requires the robot to explore, localize and map its surrounding. By solving a maze, the pertaining algorithms and behavior of the robot can be studied and improved upon. This paper describes an implementation of a maze-solving robot designed to solve a maze based on the flood-fill algorithm. Detection of walls and opening in the maze were done using ultrasonic range-finders. Algorithm for straight-line correction was based on PI(D) controller. The robot was able to learn the maze, find all possible routes and solve it using the shortest one.

IRJET, 2021

In this paper, literature survey on MAZE SOLVING ROBOT is carried on various papers which has the ability to navigate automatically in an unknown area based on its own decision. Every paper has its own methodology for designing and implementing the robot. At the end the results are compared to find the most efficient one, followed by proposed system.

2002

We present in this paper the crucial components of "Mr.ArmHandOne" project. We shall discuss topics concerning the robot architecture; the robot building process, including the mechanics and electronics solutions to the robot structure; the description of a dynamic neural network for processing the raw data coming from the sonars; the local map dynamic construction, and the overall structure of the cognitive components. We shall then describe ArmHandOne main task, consisting in £nding and getting some object in a real non engineered dynamic world. The test-bed of our research is summarized in the proposed demo: £nding and recognizing objects displaced in an unknown labyrinthine structure. The agent is initially positioned in a random place inside a maze, and his goal is to £nd, grasp and recover a required object, and taking it to an "Exit" position.

knu.edu.tw

AGV (Automated Guided Vehicle) is known as a robotic system that can move autonomously following an established path to complete a task. AMR (Autonomous Mobile Robot) is also known as a robotic system that can move autonomously to complete a task, but AMR can adapt easily to a new environment without having to follow a path that has been established before. This makes an AGV and an AMR differ. AMR has three behaviors, one of them is world modeling. World modeling is the behavior of AMR that models an unknown environment in which the robot resides. This behavior is very useful to trace dangerous places, such as ruins of building, underground planted duct pipe, etc. This work is a part of a complete research titled “A Study on Using AMR to Map An Unknown Maze”. This research focuses only on how to design a hardware of sensory and movement system. The sensory system will supply inputs to the control system. This system will “pick up” any alteration of its surrounding area information, and send them to the control system. The control system will then execute a command to move in various direction based on the movement algorithm. The discussion about the movement algorithm and all things related to it is done by Jimmy (2004) in a separate part of the whole research. The result of this research shows that the prototype can map a maze based on a appropriate communication of a sensory, a movement, and a control systems.

Machines

Autonomous robots are designed to discover and interpret their surroundings and orient themselves around obstacles to reach the destination point from an initial point. Robot autonomous navigation is a requirement for maze-solving systems, where the solver robot is required to navigate the maze area to get its desire destination location using the fastest route possible. In this paper, a new, modified wall-follower system for a maze-solving robot was proposed that overcame the infinite loop-back issue in the traditional wall-follower approaches. We also investigated and analyzed the performance of three different maze-solving algorithms and compared them with the proposed, modified wall-follower robotic system by conducting several real experiments to validate the efficiency of the developed wall-follower robotic system.

TELKOMNIKA, 2022

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.

The purpose of the project is to develop maze exploration algorithms for a multi-agent system, using autonomous robots, that allows the agents to successfully navigate through an array of different mazes based on the game Theseus and the Minotaur. Theseus and the Minotaur is a maze game in which Theseus tries to get to the exit of each maze without being eaten by the Minotaur. For every one move Theseus makes, the Minotaur can make two. The mazes become progressively harder as each maze is completed. A single intelligence system is made up of algorithms for the robots to use in order successfully simulate the Theseus and the Minotaur game. One of the robots will represent Theseus and the other robot will represent the Minotaur. The Theseus robot will work to traverse the maze while avoiding the Minotaur. The Minotaur robot will work to navigate through the maze in order to catch the Theseus robot. The goal is to have the robots simulate the Theseus and the Minotaur game without any human interaction. The next step is to validate the developed algorithms in a laboratory experiment using programmable mobile robots.

2014 IEEE International Symposium on Intelligent Control (ISIC), 2014

The paper proposes a wireless navigation mobile robot system for both path planning and trajectory execution within an indoor maze environment. This system consists of the mobile robot, trajectory planner, motion controller, visual sensor (CCD camera), ZigBee wireless communication device and a maze terrain. The camera is used to capture images of the mobile robot within the maze. Developed image processing and analyzing algorithms determine the robot's position and orientation based on color markers recognition. Markers are mounted on the top of the robot. Based on this data the implemented navigation system calculates a trajectory for the mobile robot from a starting point to a target point. The proposed navigation system is an upgrade to our previously developed system. Maze encryption and motion planning modules have been added to the previous system. Breadth First Search (BFS) and modified Depth First Search (DFS) algorithms were used for the trajectory calculation. A developed control algorithm calculates control signals in real time. These signals are sent to the robot via modules for wireless communication, causing robot motion along the calculated trajectory and eventually, the completion of the trajectory. The whole control system is realized and experimental results have been obtained. The experimental results confirm the robustness and effectiveness of the implemented control system.