Theoretical and Natural Science
- The Open Access Proceedings Series for Conferences
Theoretical and Natural Science
Vol. 18, 08 December 2023
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Researches advanced in path planning to indoor fire escape and rescue based on SLAM
* Author to whom correspondence should be addressed.
Abstract
Helping trapped people understand the external situation and provide navigation to escape the fire is the key to reducing fire casualties. Thanks to the rapid development of artificial intelligence technology, the combination of simultaneous localization and mapping (SLAM) and path planning technology has gradually become a new research hotspot, which can help provide on-site fire information, maps and navigation for trapped people and firefighters. However, improving the accuracy of SLAM techniques under harsh conditions (e.g., thick smoke, high temperature) is still an open topic. Focusing on SLAM noise reduction and path planning, in this paper, we detail the latest research progress of SLAM technology in fire escape assistance. Specifically, we first introduce the current development and application frontiers of SLAM technology, and then analyze and compare the application of SLAM technology in fire scenarios. In addition, the performance changes of the two continuous A* algorithms and the RRT algorithm during global path planning for fire scenarios are compared. Finally, we discuss the development trend of SLAM in future fire escape and rescue.
Keywords
SLAM, rescue robot, fire rescue, path planning
References
1. Torero J L. Fire-induced structural failure: the world trade center, New York[J]. Proceedings of the Institution of Civil Engineers-Forensic Engineering, 2011, 164(2): 69-77.
2. Fridolf K, Nilsson D, Frantzich H. Fire evacuation in underground transportation systems: a review of accidents and empirical research[J]. Fire technology, 2013, 49(2): 451-475.
3. Njå O, Svela M. A review of competencies in tunnel fire response seen from the first responders’ perspectives[J]. Fire safety journal, 2018, 97: 137-145.
4. Dogru S, Marques L. Using radar for grid based indoor mapping[C]//2019 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC). IEEE, 2019: 1-6.
5. bin Shamsudin A U, Mizuno N, Fujita J, et al. Evaluation of LIDAR and GPS based SLAM on fire disaster in petrochemical complexes[C]//2017 IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR). IEEE, 2017: 48-54.
6. Brunner C, Peynot T, Vidal-Calleja T. Combining multiple sensor modalities for a localisation robust to smoke[C]//2011 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, 2011: 2489-2496.
7. Grisetti G, Stachniss C, Burgard W. Improved techniques for grid mapping with rao-blackwellized particle filters[J]. IEEE transactions on Robotics, 2007, 23(1): 34-46.
8. Santos J M, Couceiro M S, Portugal D, et al. A sensor fusion layer to cope with reduced visibility in SLAM[J]. Journal of Intelligent & Robotic Systems, 2015, 80(3): 401-422.
9. Kohlbrecher S, Von Stryk O, Meyer J, et al. A flexible and scalable SLAM system with full 3D motion estimation[C]//2011 IEEE international symposium on safety, security, and rescue robotics. IEEE, 2011: 155-160.
10. Steux B, El Hamzaoui O. tinySLAM: A SLAM algorithm in less than 200 lines C-language program[C]//2010 11th International Conference on Control Automation Robotics & Vision. IEEE, 2010: 1975-1979.
11. Carlone L, Aragues R, Castellanos J A, et al. A linear approximation for graph-based simultaneous localization and mapping[C]//Robotics: Science and Systems. 2012, 7: 41-48.
12. Vincent R, Limketkai B, Eriksen M. Comparison of indoor robot localization techniques in the absence of GPS[C]//Detection and sensing of mines, explosive objects, and obscured targets XV. SPIE, 2010, 7664: 606-610.
13. Wu R, Pike M, Chai X, et al. Gaitpdr: Using Gait Analysis for Heading Estimation in Pdr Based Indoor Localization Systems[J]. Available at SSRN 4045876.
14. Yu J, Na Z, Liu X, et al. WiFi/PDR-integrated indoor localization using unconstrained smartphones[J]. EURASIP Journal on Wireless Communications and Networking, 2019, 2019(1): 1-13.
15. Zhang Z, Liu J, Wang L, et al. An enhanced smartphone indoor positioning scheme with outlier removal using machine learning[J]. Remote Sensing, 2021, 13(6): 1106.
16. Jin J, Tang L. Optimal path planning for arable farming, 2006 Portland, Oregon, July 9-12,2006.
17. Xuexi Zhang, Jiajun Lai, Dongliang Xu, Huaijun Li, Minyue Fu, "2D Lidar-Based SLAM and Path Planning for Indoor Rescue Using Mobile Robots", Journal of Advanced Transportation, vol. 2020, Article ID 8867937, 14 pages, 2020.
18. Li S, Feng C, Niu Y, Shi L, Wu Z, Song H. A Fire Reconnaissance Robot Based on SLAM Position, Thermal Imaging Technologies, and AR Display. Sensors (Basel). 2019 Nov 18;19(22):5036. doi: 10.3390/s19225036. PMID: 31752251; PMCID: PMC6891496.
Data Availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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- Volume Title
- Proceedings of the 2nd International Conference on Computing Innovation and Applied Physics
- ISBN (Print)
- 978-1-83558-201-5
- ISBN (Online)
- 978-1-83558-202-2
- Published Date
- 08 December 2023
- Series
- Theoretical and Natural Science
- ISSN (Print)
- 2753-8818
- ISSN (Online)
- 2753-8826
- DOI
- 10.54254/2753-8818/18/20230360
- Copyright
- 08 December 2023
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited