Maze Solving Algorithms for Micro Mouse

Mishra, Shivendra; Bande, Pankaj

doi:10.1109/sitis.2008.104

Cited by 77 publications

(49 citation statements)

References 7 publications

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“…The Flood Fill algorithm uses the concept of water always flowing from a higher elevation to a lower one [3] [4]. It applies this concept by assigning each cell in the maze a value that represents how far the cell is from the center.…”

Section: A Flood Fill Algorithmmentioning

confidence: 99%

“…4c show only the relevant portion of the maze. Fig 4a shows the distance values when the micromouse reaches cell (4,1) where the distance update is necessary. Comparing this distance update process will reveal the algorithms' differences.…”

Section: Appendix Distance Update Algorithms Comparisonmentioning

confidence: 99%

“…The revised distance update algorithm will push all neighbors cells (5, 1), (3,1), (4,0), and (4, 2) onto the stack whereas S. Benkovic's distance update algorithm will push only open neighbor cells (4, 0) and (4, 2). As a result, cell (3, 1) distance value will not be updated in his algorithm.…”

Section: Appendix Distance Update Algorithms Comparisonmentioning

confidence: 99%

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Quantitative Comparison of Flood Fill and Modified Flood Fill Algorithms

Law¹

2013

IJCTE

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Abstract-Flood fill algorithm has won first places in the international micromouse competitions. To save computation time, the modified flood fill algorithm is often coded. Yet, the literature search reveals the scarcity of the quantitative details of the two algorithms. This article attempts to discuss their differences and uses Maze-solver simulator to collect and tabulate the maze-run statistics for various popular mazes. It will discuss these statistics and various aspects of the flood fill algorithm modifications.Index Terms-Flood fill algorithm, maze simulation, micromouse competition, modified flood fill algorithm.

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Section: A Flood Fill Algorithmmentioning

confidence: 99%

Section: Appendix Distance Update Algorithms Comparisonmentioning

confidence: 99%

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Quantitative Comparison of Flood Fill and Modified Flood Fill Algorithms

Law¹

2013

IJCTE

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“…Once after storing the shortest distant path it travels to the shortest path every time it is made to solve the same maze. The designed robot uses two algorithms which are Left straight Right Back (LSRB) algorithm and Right Straight Left Back (RSLB) algorithm [3].The basic application of the designed robot can be for navigation purpose in which the robot once after traversing all the directions automatically follows the shortest path all the time [4]. To solve the maze we use LSRB and RSLB algorithm.…”

Section: Introductionmentioning

confidence: 99%

Shortest Distance Maze Solving Robot

Islam¹

2016

IJRET

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In this paper, the design of maze solving robot which has the ability to navigate automatically in an unknown area based on its own decision is presented. For the proposed design algorithm, a wall following technique based on LSRB and RSLB algorithm is used. The designed robot obtains input from ultrasonic sensor, Infra-red sensor and wheel rotation encoders and then make decision for solving maze. It has the capability to solve the maze by taking the shortest distant path and it stores the details for the further reference also. The designed robot has the ability to learn any arbitrary maze and find the possible shortest route for solving it. The best application of this designed robot could be for navigational purposes

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“…The competition has resulted in a number of papers describing different approaches to solving the maze. One of these [35] examines three popular methods: the wall follower, Dijkstra's algorithm, and the flood fill algorithm. The authors briefly describe each algorithm and then discuss the relevant drawbacks.…”

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confidence: 99%

Building Maze Solutions with Computational Dreaming

Jackson

Paul

2017

IEEE Micro

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Modern parallel computing techniques are subject to poor scalability. Their performance tends to suffer diminishing returns and even losses with increasing parallelism. Some methods of intelligent computing, such as neural networks and genetic algorithms, lend themselves well to massively parallel systems but come with other drawbacks that can limit their usefulness such as the requirement of a training phase and/or sensitivity to randomness. This thesis investigates the feasibility of a novel method of intelligent parallel computing by implementing a true multiple instruction stream, single data stream (MISD) computing system that is theoretically nearly perfectly scalable. Computational dreaming (CD) is inspired by the structure and dreaming process of the human brain. It examines previously observed input data during a "dream phase" and is able to develop and select a simplified model to use during the day phase of computation. Using mazes as an example problem space, a CD simulator is developed and successfully used to demonstrate the viability and robustness of CD. Experiments that focused on CD viability resulted in the CD system solving 15% of mazes (ranging from small and simple to large and complex) compared with 2.2% solved by random model selection. Results also showed that approximately 50% of successful solutions generated match up with those that would be generated by algorithms such as depth first search and Dijkstra's algorithm. Experiments focusing on robustness performed repeated trials with identical parameters. Results demonstrated that CD is capable of achieving this result consistently, solving over 32% of mazes across 10 trials compared to only 3.6% solved by random model selection. A significant finding is that CD does not get stuck on local minima, always converging on a solution model. Thus, CD has the potential to enable significant contributions to computing by potentially finding elegant solutions to, for example, NP-hard or previously intractable problems.iii

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Maze Solving Algorithms for Micro Mouse

Cited by 77 publications

References 7 publications

Quantitative Comparison of Flood Fill and Modified Flood Fill Algorithms

Quantitative Comparison of Flood Fill and Modified Flood Fill Algorithms

Shortest Distance Maze Solving Robot

Building Maze Solutions with Computational Dreaming

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