Abstract
We consider the problem of robot global path planning using traditional A* algorithm based on ROS. By means of an improved A* algorithm, we are able to solve the safety problem of robots. The algorithm calculates the threat value of obstacles to the robot and adds it to the evaluation function. During the execution of the algorithm, the security threat value of the node is calculated according to the shortest distance between the node and obstacle, adding the value to the corresponding node evaluation, finding the best path through the evaluation function. The generated path is smoothed with the two-order Bezier curve. This algorithm improves the safety performance and the optimality of the path.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Zhu D, Latombe JC (1991) New heuristic algorithms for efficient hierarchical path planning. IEEE Trans. Robot Autom. 7(1):9e20
Yang, X.S., Deb, S.: Cuckoo search via Levy flights. In: Nature and Biologically Inspired Computing, NaBIC 2009, IEEE World Congress, p. 210e4 (2009)
Holland JH (1972) Adaptation in Natural and Artificial Systems. University of Michigan Press, Ann Arbor, MI
Shing, M.T., Parkar, G.B.: Genetic algorithm for the development of real-time multi-heuristic search strategies. In: Proc. 5th Conf. On genetic algorithm. Morgan Kaumann Publication, Los Aitos, California, p. 565e70 (1993)
Jing Xiao Z, Michalewicz LZ, Trojanowski K (1997) Adaptive evolutionary planner/navigator for mobile robots. IEEE Trans. Evol. Comput. 1(1):18–28
Kang X, Yue Y, Li D, Maple C (2011) Genetic algorithm based solution to dead problems in robot navigation. Int. J. Comput. Appl. Technol. 41(3/4):177e84
Quigley, M., Gerkey, B., Smart, W.D.: Programming Robots with ROS. O’Reilly Media, Inc., 1005 Gravenstein Highway North, Sebastopol, CA 95472
Acknowledgement
This work has been supported by the Key Research and Development Program of Shandong Province (2019GGX104079), Natural Science Foundation of Shandong Province (ZR2018QF005), Qilu University of Technology (Shandong Academy of Science) Special Fund Program for International Cooperative Research (QLUTGJHZ2018019), Key Research and Development Program of Shandong Province (2019GGX104091), Natural Science Foundation of Shandong Province (ZR2018LF011), Science, education and industry integration innovation pilot project of Qilu University of Technology (Shandong Academy of Sciences) (2020KJC-ZD04).
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Feng, D., Deng, L., Sun, T., Liu, H., Zhang, H., Zhao, Y. (2022). Global Path Planning Based on an Improved A* Algorithm in ROS. In: Jing, X., Ding, H., Wang, J. (eds) Advances in Applied Nonlinear Dynamics, Vibration and Control -2021. ICANDVC 2021. Lecture Notes in Electrical Engineering, vol 799. Springer, Singapore. https://doi.org/10.1007/978-981-16-5912-6_84
Download citation
DOI: https://doi.org/10.1007/978-981-16-5912-6_84
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-16-5911-9
Online ISBN: 978-981-16-5912-6
eBook Packages: EngineeringEngineering (R0)