An Efficient Algorithm for Robot Maze-Solving

Dang, Hongshe; Song, Jinguo; Guo, Qin

doi:10.1109/ihmsc.2010.119

Cited by 28 publications

(9 citation statements)

References 1 publication

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“…As there are certain parts in the maze where the robot can go only straight forward, when the robot is inside these parts, it does not need to perform all four steps of maze solving which is updating the wall, flooding the maze, determining which turn to be taken and moving to the next cell. This proved to be more efficient than the traditional approach of just using the flood-fill algorithm [5]. Whereas, Patel et.al.…”

Section: Related Workmentioning

confidence: 99%

Aerial View Based Guidance System

Wasti

Tripathi

Regmi

et al. 2020

Jnl Innov. Engin. Educ.

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With the limited amount of resources and roads available, traffic congestion seems to be the current leading problem for urban areas. Reliance on the traditional vehicular navigation systems seems to a huge contributing factor, which simply cannot meet the present demand for better traffic management. While the existent navigation system relies on the Global Navigation Satellite System (GNSS) and predefined historic navigation data, a real time optimal pathfinding navigation system has been lacking. We have proposed a close to a real-time system that calculates an optimal path from start to destination using floodfill algorithm and provides guidance to ground vehicles. A camera hovering over the top provides a bird’s eye view and via the Hyper Text Transfer Protocol (HTTP) on top of 802.11n protocol, transfers aerial view from the airborne device to Unmanned Ground Vehicle (UGV) where the actual computer vision processing is done in a local processor. The use of floodfill algorithm although requires an image that contains the whole maze but makes the system far more efficient. This makes it real time and efficient which may be further improved and integrated with actual traffic scenarios.

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Section: Related Workmentioning

confidence: 99%

Aerial View Based Guidance System

Wasti

Tripathi

Regmi

et al. 2020

Jnl Innov. Engin. Educ.

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show abstract

“…Their work realized that a number of channels could exist inside the maze, which means when the robot enters the maze, it can only move to the cell in front. All four steps can be performed using this technique [3].…”

Section: Related Workmentioning

confidence: 99%

Autonomous Navigation of Mobile Robot Based on Flood Fill Algorithm

Jabbar¹

2016

IJEEE

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The autonomous navigation of robots is an important area of research. It can intelligently navigate itself from source to target within an environment without human interaction. Recently, algorithms and techniques have been made and developed to improve the performance of robots. It's more effective and has high precision tasks than before. This work proposed to solve a maze using a Flood fill algorithm based on real time camera monitoring the movement on its environment. Live video streaming sends an obtained data to be processed by the server. The server sends back the information to the robot via wireless radio. The robot works as a client device moves from point to point depends on server information. Using camera in this work allows voiding great time that needs it to indicate the route by the robot.

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“…As there are channels in the maze where the robot is forced to go only straight forward, when the robot is inside these channels, it does not need to perform all four steps of mazesolving which is updating the wall, flooding the maze, determining which turn to be taken and moving to the next cell. To reduce execution time, it only flood the maze when there is a turn [4].…”

Section: Related Workmentioning

confidence: 99%

Design and Implementation of a Robot for Maze-Solving using Flood-Fill Algorithm

Elshamarka¹,

Saman²

2012

IJCA

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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. General TermsAutonomous navigation, maze-solving, flood-fill algorithm, ultrasonic sensor, PI(D) controller.

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An Efficient Algorithm for Robot Maze-Solving

Cited by 28 publications

References 1 publication

Aerial View Based Guidance System

Aerial View Based Guidance System

Autonomous Navigation of Mobile Robot Based on Flood Fill Algorithm

Design and Implementation of a Robot for Maze-Solving using Flood-Fill Algorithm

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