An Stable Intelligence Medical Trolley Path Planning System Based on Improved Breadth First Search Algorithm
DOI:
https://doi.org/10.54097/hset.v71i.12690Keywords:
Path planning, trolley, intelligence, hospital.Abstract
Intelligence medical trolley path planning system is a comprehensive intelligent system that integrates many functions such as environmental perception, decision planning and motion control. Due to the characteristics of low speed, simple operating conditions, and priority information, it is unmanned one of the first scenes that can be achieved, with high research value. Although Intelligence Medical Trolley System has been widely developed and developed, many problems still need to be resolved.For example, the search path is not the optimal path resulting in reduced efficiency, or the algorithm is not stable enough, causing the trolley to deviate from the running path.The Path Planning algorithm is the core content of the robot. This article focuses on the improvement of path planning algorithm and determine the feasibility of the algorithm through simulation experiments and optimize. The feasibility of the algorithm is confirmed and optimized by simulation experiments. Finally, through the infrared sensor and the physical sign combine the reality with the algorithm results, and verifies the path planning algorithm with the mobile robot entity. This design uses c++ as the development language, and then uses Arduino as the development platform, lets the mobile robot move according to the path which produced by the algorithm. The experimental results show that the system based on Breath First Search (BFS) algorithm is feasible and can be applied to the working environment of hospital.
Downloads
References
M. Nicole, M. Kathleen J, and P. David. “The Effect of Population Aging on Economic Growth, the Labor Force, and Productivity" American economic journal: macroeconomics, vol. 15, no. 2, pp. 306-32, April 2023
X. Guo, M. Zhou, S. Liu and L. Qi, "Lexicographic multiobjective scatter search for the optimization of sequence-dependent selective disassembly subject to multiresource constraints", IEEE Trans. Cybern., vol. 50, pp. 3307-3317, Jul. 2020.
J. Han and Y. Seo, "Mobile robot path planning with surrounding point set and path improvement", Appl. Soft Comput., vol. 57, pp. 35-47, Aug. 2017
W. Wu, S. Bhattacharya and A. Prorok, "Multi-Robot Path Deconfliction through Prioritization by Path Prospects", IEEE International Conference on Robotics and Automation, 2020.
A. Bircher, M. Kamel, K. Alexis and H. Oleynikova, "Receding horizon path planning for 3D exploration and surface inspection", Auton. Robots, vol. 42, no. 2, pp. 291-306, 2018.
A. H. Qureshi and Y. Ayaz, "Potential functions-based sampling heuristic for optimal path planning", Auton. Robots, vol. 40, no. 6, pp. 1079-1093, Nov. 2015.
Y. Qian, F. Wang, J. Li, L. Shi and K. Cai, "User association and path planning for UAV-aided mobile edge computing with energy restriction", IEEE Wireless Commun. Lett., vol. 8, no. 5, pp. 1312-1315, Oct. 2019
C. Zhong, W. Chen. Research on Hybrid path Planning Algorithm for Mobile Robots. Automatic Instrumentation, vol. 42, no. 9, pp. 61-66, 2016.
Q. Jia, X. Wang, "An improved potential field method for path planning", Proc. Chin. Control Decis. Conf., pp. 2265-2270, May 2010.
M. Rickert, A. Sieverling and O. Brock, "Balancing exploration and exploitation in sampling-based motion planning", IEEE Trans. Robot., vol. 30, no. 6, pp. 1305-1317, Dec. 2014
Downloads
Published
Issue
Section
License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.







