Skip to main content
Log in

Robot SLAM with Ad hoc wireless network adapted to search and rescue environments

适应于搜救环境利用Ad hoc 无线网络的机器人SLAM

  • Published:
Journal of Central South University Aims and scope Submit manuscript

Abstract

An innovative multi-robot simultaneous localization and mapping (SLAM) is proposed based on a mobile Ad hoc local wireless sensor network (Ad-WSN). Multiple followed-robots equipped with the wireless link RS232/485 module act as mobile nodes, with various on-board sensors, Tp-link wireless local area network cards, and Tp-link wireless routers. The master robot with embedded industrial PC and a complete robot control system autonomously performs the SLAM task by exchanging information with multiple followed-robots by using this self-organizing mobile wireless network. The PC on the remote console can monitor multi-robot SLAM on-site and provide direct motion control of the robots. This mobile Ad-WSN complements an environment devoid of usual GPS signals for the robots performing SLAM task in search and rescue environments. In post-disaster areas, the network is usually absent or variable and the site scene is cluttered with obstacles. To adapt to such harsh situations, the proposed self-organizing mobile Ad-WSN enables robots to complete the SLAM process while improving the performances of object of interest identification and exploration area coverage. The information of localization and mapping can communicate freely among multiple robots and remote PC control center via this mobile Ad-WSN. Therefore, the autonomous master robot runs SLAM algorithms while exchanging information with multiple followed-robots and with the remote PC control center via this local WSN environment. Simulations and experiments validate the improved performances of the exploration area coverage, object marked, and loop closure, which are adapted to search and rescue post-disaster cluttered environments.

摘要

本文提出了一种基于移动Ad hoc 局域无线传感器网络 (Ad-WSN) 的创新型多机器人同时定位 与地图创建 (SLAM)。通过装备无线连接模块RS232/485 的多机器人作为移动的节点,将机器人车载 各种传感器、Tp-link 无线局域网卡和Tp-link 无线路由器等部署覆盖到整个探索环境区域;具有内置 工业PC (IPC) 的主机器人和完全自主控制系统,通过使用该移动Ad-WSN 无线传感器局域网,与多 机器人交换信息以自主执行SLAM 任务;位于安全环境的远程控制中心可以监控现场多机器人SLAM 执行情况,并能够对机器人提供直接运动控制,以保障恶劣环境下机器人的运行安全。移动Ad-WSN 无线传感器局域网弥补了在搜索和救援 (SAR) 环境中,机器人执行SLAM 任务时通常GPS 定位信号 的易变或缺失。灾后SAR 环境中,信息交换网络通常不存在或不可靠,搜救现场充满障碍物。为了 适应恶劣SAR 环境的苛刻条件,本文提出的多机器人自组织移动Ad-WSN 局域网能够完全自主执行 SLAM 过程,同时提高了搜救兴趣目标 (OOI) 辨识、SLAM 信号的探索区域面积覆盖性能。定位和 地图构建信息可以通过该移动Ad-WSN 无线局域网在多机器人之间,以及与远程PC 控制中心之间进 行传输和通讯。因此,自主机器人能够在与多随从机器人交换信息的同时运行SLAM 算法,并通过该 无线局域网与远程PC 控制中心交换信息。仿真和实验验证了自主机器人移动Ad-WSN 无线局域网 SLAM 适应探索区域面积覆盖、搜救目标定位标记、运动轨迹闭环重访点检测等适应灾后SAR 环境 的改进性能。

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. BAILEY T, DURRANT-WHYTE H. Simultaneous localization and mapping (SLAM): Part II [J]. IEEE Robot & Automation Mag, 2006, 13(3): 108–117.

    Article  Google Scholar 

  2. DURRANT-WHYTE H, BAILEY T. Simultaneous localization and mapping (SLAM): Part I [J]. IEEE Robot & Automation Mag, 2006, 13(2): 99–108.

    Article  Google Scholar 

  3. FERWORN A, TRAN J, UFKES A. Establishing network connectivity under rubble using a hybrid and wireless approach [C]//Safety, Security, and Rescue Robot (SSRR). IEEE International Symposium, 2012: 1–4.

    Google Scholar 

  4. ALZAQ H, KABADAYI S. Mobile robot comes to the rescue in a WSN [C]//2013 IEEE 24th International Symposium on Personal, Indoor and Mobile Radio Communications: Mobile and Wireless Networks. 2013: 1977–1982.

    Book  Google Scholar 

  5. REID R, CANN A, MEIKLEJOHN C. Cooperative multi-robot navigation, exploration, mapping and object detection with ROS [C]//2013 IEEE Intelligent Vehicles Symposium (IV). Gold Coast, Australia, 2013: 1083–1088.

    Google Scholar 

  6. NAIM I. A co-operative network of rescue robots for disaster management [C]//Communication Science Committee (CSC) 400: Info Tech Research Group (ITFG) Miniproposal, 2011: 1–4.

    Google Scholar 

  7. HUR H, AHN H S. Unknown input H observer-based localization of a mobile robot with sensor failure [J]. IEEE/ASME Transactions on Mechatronics, 2014, 19(6): 1830–1838.

    Article  Google Scholar 

  8. TUNA G, GUMGOR V C, GULEZ K. An autonomous wireless sensor network deployment system using mobile robots for human existence detection in case of disasters [J]. Ad Hoc Networks, 2014, 13(1): 54–68.

    Article  Google Scholar 

  9. WICHMANN A, OKKALIOGLU B D, KORKMAZ T. The integration of mobile (tele) robotics and wireless sensor networks: A survey [J]. Computer Communications, 2014, 51(5): 21–35.

    Article  Google Scholar 

  10. CARLI M, PANZIERI S, PASCUCCI F. A joint routing and localization algorithm for emergency scenario [J]. Ad Hoc Networks, 2014, 13(1): 19–33.

    Article  Google Scholar 

  11. KUNTZE H B, FREY C, EMTER T. Situation responsive networking of mobile robots for disaster management [C]//Conference ISR ROBOTIK. Berlin, German, 2014: 313–320.

    Google Scholar 

  12. TUNA G, GÜNGÖR V Ç, POTIRAKIS S M. Wireless sensor network-based communication for cooperative simultaneous localization and mapping [J]. Computers & Electrical Engineering, 2014, 41(4): 4074–4085.

    Google Scholar 

  13. LA H M. Cooperative and active sensing in mobile sensor networks for scalar field mapping [J]. IEEE Transactions on Systems Man & Cybernetics Systems, 2015, 45(1): 831–836.

    Google Scholar 

  14. FERNNANDES A S, COUCEIRO M S, PORTUGAL D. Ad hoc communication in teams of mobile robots using zigbee technology [J]. Computer Applications in Engineering Education, 2015, 23(5): 733–745.

    Article  Google Scholar 

  15. HIROMOTO R E, SACHENKO A, KOCHAN V. Mobile Ad Hoc wireless network for pre-and post-emergency situations in nuclear power plant [C]//International Symposium on Wireless Systems Within the Conferences on Intelligent Data Acquisition and Advanced Computing Systems. Idaacs-Sws, Offenburg, Germany, 2014: 92–96.

    Google Scholar 

  16. AGHILI F, SALERNO A. Driftless 3-D attitude determination and positioning of mobile robots by integration of IMU with two RTK GPSs [J]. IEEE/ASME Transactions on Mechatronics, 2013, 18(1): 21–31.

    Article  Google Scholar 

  17. HAN S B, KIM J H, MYUNG H. Landmark-based particle localization algorithm for mobile robots with a fish-eye vision system [J]. IEEE/ASME Transactions on Mechatronics, 2013, 18(6): 1745–1756.

    Article  Google Scholar 

  18. LUO R C, CHEN O. Wireless and pyroelectric sensory fusion system for indoor human/robot localization and monitoring [J]. IEEE/ASME Transactions on Mechatronics, 2013, 18(3): 5649–5654.

    Google Scholar 

  19. KLEINER A, DOMHEGE C. Real-time localization and elevation mapping within urban search and rescue scenarios [J]. J Field Robot, 2007, 24(8): 723–745.

    Google Scholar 

  20. GOUVEIA B D, PORTUGAL D, SILVA D C. Computation sharing in distributed robotic systems: A case study on SLAM [J]. IEEE Transactions on Automation Science & Engineering, 2014, 12(2): 410–422.

    Article  Google Scholar 

  21. ELIAZAR A I, PARR R. Hierarchical linear/constant time SLAM using particle filters for dense maps [C]//Advances in Neural Information Processing Systems. Vancouver, British Columbia, Canada, 2005: 1–8.

    Google Scholar 

  22. RUSSO S, HARADA K, RANZANI T. Design of a robotic module for autonomous exploration and multimode locomotion [J]. IEEE/ASME Transactions on Mechatronics, 2013, 18(6): 1757–1766.

    Article  Google Scholar 

  23. BEZZO N, GRIFFIN B, CRUZ P. A cooperative heterogeneous mobile wireless mechatronic system [J]. Mechatronics IEEE/ASME Transactions on Mechatronics, 2014, 19(1): 20–31.

    Article  Google Scholar 

  24. SHIH C Y, CAPITÁN J, MARRÓN P J, VIGURIA A. On the Cooperation between Mobile Robots and Wireless Sensor Networks [J]. Cooperative Robots and Sensor Networks, Studies in Computational Intelligence, 2014, 55(4): 67–86.

    Google Scholar 

  25. LI Jie, SUN Zhi, SHI Bo, GONG Er XIE Hong. Relay movement control for maintaining connectivity in aeronautical ad hoc networks [J]. Journal of Central South University, 2016, 23(4): 850–858.

    Article  Google Scholar 

  26. HUA Cheng, DOU Li, FANG Hao, FU Hao. A novel algorithm for SLAM in dynamic environments using landscape theory of aggregation [J]. Journal of Central South University, 2016, 23(10): 2587–2594.

    Article  Google Scholar 

  27. YU Jin, FENG Wei, TANG Di, LIU Hao. Comparison of dynamic Bayesian network approaches for online diagnosis of aircraft system [J]. Journal of Central South University, 2016, 23(11): 2926–2934.

    Article  Google Scholar 

  28. BIRK A, SCHWERTFEGER S, PATHAK K. A networking framework for teleoperation in safety, security, and rescue robotics [J]. Wireless Communications in Networked Robot, 2009, 16(1): 6–13.

    Article  Google Scholar 

  29. WANG Y, CHEN W, WANG J, WANG H. Active global localization based on localizability for mobile robots [J]. Robotica, 2015, 33(1): 1609–1627.

    Article  MathSciNet  Google Scholar 

  30. WANG N, MA S, LI B, WANG M. Subjective exploration for simultaneous localization and mapping used in ruins [C]//The 5th Annual IEEE International Conference on Cyber Technology in Automation, Control and Intelligent Systems, Shenyang. China, 2015.

    Google Scholar 

  31. SCHLEICHER D, BERGASA L M, OCAÑA M. Real-time hierarchical outdoor SLAM based on stereovision and GPS fusion [J]. IEEE Trans Intell Trans Syst, 2009, 10(3): 440–452.

    Article  Google Scholar 

  32. CHEN S Y. Kalman filter for robot vision: A survey [J]. IEEE Transactions on Industrial Electronics, 2012, 59(11): 4409–4420.

    Article  Google Scholar 

  33. REENTOV E, MESSIER G G, MAGIEROWSKI S. Evaluating wireless network effects for SLAM robot map making [C]//IEEE Communications Society Subject Matter Experts for Publication in Proceedings of the IEEE Globecom. Canada, 2010: 1–5.

    Book  Google Scholar 

  34. BRAND C, SCHUSTER M J, HIRSCHNULLER H. Stereovision based obstacle mapping for indoor/outdoor SLAM [C]//IROS. Chicago, USA 2014: 1846–1853.

    Google Scholar 

  35. KIM A, EUSTICE R M. Perception-driven navigation: active visual SLAM for robotic area coverage [C]//2013 IEEE Int Conf Robotics and Automation (ICRA). Karlsruhe, Germany, 2013: 3196–3203.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Cheng-jin Zhang  (张承进).

Additional information

Foundation item: Projects(61573213, 61473174, 61473179) supported by the National Natural Science Foundation of China; Projects(ZR2015PF009, ZR2014FM007) supported by the Natural Science Foundation of Shandong Province, China; Project(2014GGX103038) supported by the Shandong Province Science and Technology Development Program, China; Project(2014ZZCX04302) supported by the Special Technological Program of Transformation of Initiatively Innovative Achievements in Shandong Province, China

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, Hl., Zhang, Cj., Song, Y. et al. Robot SLAM with Ad hoc wireless network adapted to search and rescue environments. J. Cent. South Univ. 25, 3033–3051 (2018). https://doi.org/10.1007/s11771-018-3972-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11771-018-3972-8

Key words

关键词

Navigation