Abstract
Indoor path planning technology has become more and more extensive, e.g., indoor navigation and real-time scene construction. There are many difficulties in the existing indoor path planning researches, including the slower searching speed and the higher storage space cost, which is inability to meet user requirements in a complex indoor environment. This paper proposes a path planning method based on indoor maps. First, the indoor environment is hierarchically modelled, and then the corresponding path searching algorithm is developed to obtain the optimal path. Experimental results show that using the path planning method designed in this paper can effectively solve the above problems.
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
Cho, K., Suh, J., Tomlin, C.J., Oh, S.: Cost-aware path planning under co-safe temporal logic specifications. IEEE Robot. Autom. Lett. 2(4), 2308–2315 (2017)
Xiong, Q., Zhu, Q., Zlatanova, S., Zhiqiang, D., Zhang, Y., Zeng, L.: Multi-level indoor path planning method. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 40(4), 19 (2015)
Peng, B., Lü, Z., Cheng, T.C.E.: A tabu search/path relinking algorithm to solve the job shop scheduling problem. Comput. Oper. Res. 53, 154–164 (2015)
Valencia, R., Andrade-Cetto, J.: Path planning in belief space with pose SLAM. Mapping, Planning and Exploration with Pose SLAM. STAR, vol. 119, pp. 53–87. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-60603-3_4
Yu, L., Long, Z., Xi, N., Jia, Y., Ding, C.: Local path planning based on ridge regression extreme learning machines for an outdoor robot. In: 2015 IEEE International Conference on Robotics and Biomimetics (ROBIO), pp. 745–750. IEEE (2015)
Hossain, M.A., Ferdous, I.: Autonomous robot path planning in dynamic environment using a new optimization technique inspired by bacterial foraging technique. Robot. Auton. Syst. 64, 137–141 (2015)
Dijkstra, E.W.: A note on two problems in connexion with graphs. Numer. math. 1(1), 269–271 (1959)
Singh, Y., Sharma, S., Sutton, R., Hatton, D.C.: Optimal path planning of an unmanned surface vehicle in a real-time marine environment using dijkstra algorithm (2017)
Goldberg, A., Radzik, T.: A heuristic improvement of the Bellman-Ford algorithm. Technical report, STANFORD UNIV CA DEPT OF COMPUTER SCIENCE (1993)
Hagelbäck, J.: Hybrid pathfinding in starcraft. IEEE Trans. Comput. Intell. AI Games 8(4), 319–324 (2016)
Harabor, D.D., Grastien, A., et al.: Online graph pruning for pathfinding on grid maps. In: AAAI (2011)
Zhou, K., Lingli, Y., Long, Z., Mo, S.: Local path planning of driverless car navigation based on jump point search method under urban environment. Futur. Internet 9(3), 51 (2017)
Acknowledgements
This work is supported by the Natural Science Foundation of Heilongjiang Province in China (No. F2016028, F2016009, F2015029, F2015045), the Youth Innovation Talent Project of Harbin University of Commerce in China (No. 2016Q N052), the Support Program for Young Academic Key Teacher of Higher Education of Heilongjiang Province (No. 1254G030), the Young Reserve Talents Research Foundation of Harbin Science and Technology Bureau (2015RQQXJ082), and the Fundamental Research Fund for the Central Universities in China (No. HEUCFM180604).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Li, J., Zhang, L., Zhao, Q., Wang, H., Lv, H., Feng, G. (2018). A Heuristic Indoor Path Planning Method Based on Hierarchical Indoor Modelling. In: Zhou, Q., Miao, Q., Wang, H., Xie, W., Wang, Y., Lu, Z. (eds) Data Science. ICPCSEE 2018. Communications in Computer and Information Science, vol 902. Springer, Singapore. https://doi.org/10.1007/978-981-13-2206-8_38
Download citation
DOI: https://doi.org/10.1007/978-981-13-2206-8_38
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-2205-1
Online ISBN: 978-981-13-2206-8
eBook Packages: Computer ScienceComputer Science (R0)