Research on the optimum path — Taking the hospital delivery robot as an example

Guodong Liu

doi:10.54254/2755-2721/16/20230871

Research Article

Open access

Published on 23 October 2023

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Liu,G. (2023). Research on the optimum path — Taking the hospital delivery robot as an example. Applied and Computational Engineering,16,86-91.

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Research on the optimum path — Taking the hospital delivery robot as an example

Guodong Liu *^,1,

¹ University College London

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2755-2721/16/20230871

Abstract

Medical delivery robot refers to the delivery robot used in the medical field. Compared with ordinary delivery robots, the medical delivery robot needs to work in an environment with many people, which means that it needs to deal with many random obstacles at any time. This article will discuss automatically avoiding obstacles, and formulate and compare algorithms to analyze the advantages and disadvantages of automatic road exploration algorithms of different algorithms. In order to accomplish this goal, this paper will use Matlab as the main development tool and use the A-star algorithm and the Euclid algorithm as the main heuristics in the main mathematical model of the program. This program needs to be able to complete the obstacle avoidance task in a map with random size, random position, random shape, and random number of obstacles, and be able to reach the end point from the starting point. In addition, this paper will also discuss the efficiency of the A-star algorithm and the Dijkstra algorithm in obstacle avoidance and route planning, and demonstrate why the A-star algorithm is more efficient by taking time and congestion indicators.

Keywords

delivery robot, pathfinding robot, A* algorithm, Dijkstra algorithm

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References

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Cite this article

Liu,G. (2023). Research on the optimum path — Taking the hospital delivery robot as an example. Applied and Computational Engineering,16,86-91.

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About volume

Volume title: Proceedings of the 5th International Conference on Computing and Data Science

Conference website: https://2023.confcds.org/

ISBN：978-1-83558-023-3(Print) / 978-1-83558-024-0(Online)

Conference date: 14 July 2023

Editor：Marwan Omar, Roman Bauer, Alan Wang

Series: Applied and Computational Engineering

Volume number: Vol.16

ISSN：2755-2721(Print) / 2755-273X(Online)

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