Skip to main content
Log in

Aerial Wilderness Search and Rescue with Ground Support

  • Published:
Journal of Intelligent & Robotic Systems Aims and scope Submit manuscript

Abstract

Unmanned aerial vehicles (UAVs) have been proposed for a wide range of applications. Their use in wilderness search and rescue (WiSAR), in particular, has been investigated for fast search-area coverage from a high vantage point. The probability of success in such searches, however, can be further improved utilizing cooperative systems that employ both UAVs and unmanned ground vehicles (UGVs). In this paper, we present a new coordinated-search planning method, for collaborative UAV-UGV teams. The proposed method, particularly developed for WiSAR, considers the search area to be continuously growing and that the search is sparse. It is also assumed that targets detected by UAVs must be identified by a ground-level searcher. The UAV/UGV motion-planning method presented herein, therefore, has two major components: (i) coordinated search and (ii) joint target identification. The novelty of the proposed method lies in its use of (i) time-dependent target-location iso-probability curves, and (ii) an effective and efficient coordinated target-identification algorithm. The method has been validated via numerous simulated WiSAR searches for varying scenarios. Furthermore, extensive comparative experiments with other methods have shown that our method has higher rates of target detection and shorter search times, significantly outperforming alternative techniques by 75% – 255% in terms of target detection probability.

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. Navia, J., Mondragon, I., Patino, D., Colorado, J.: Multispectral Mapping in Agriculture: Terrain Mosaic Using an Autonomous Quadcopter UAV. In: Proc. Int. Conf. Unmanned Aircraft Syst. pp. 1351–1358, Arlington (2016)

  2. Zhang, G., Shang, B., Chen, Y., Moyes, H.: SmartCaveDrone: 3D Cave Mapping Using UAVs as Robotic Co-Archaeologists. In: Proc. Int. Conf. Unmanned Aircraft Syst. pp. 1052–1057. Miami (2017)

  3. Rasmussen, S., Kalyanam, K., Kingston, D.: Field Experiment of a Fully Autonomous Multiple UAV/UGS Intruder Detection and Monitoring System. In: Proc. Int. Conf. Unmanned Aircraft Syst. pp. 1293–1302., Arlington, VA, USA (2016)

  4. Kang, D., Cha, Y.-J.: Autonomous UAVs for Structural Health Monitoring Using Deep Learning and an Ultrasonic Beacon System with Geo-Tagging. Comput.-Aided Civ. Infrastruct. Eng. 33, 885–902 (2018). https://doi.org/10.1111/mice.12375

    Article  Google Scholar 

  5. Leira, F.S., Johansen, T.A., Fossen, T.I.: A UAV Ice Tracking Framework for Autonomous Sea Ice Management. In: Proc. Int. Conf. Unmanned Aircraft Syst. pp. 581–590, Miami (2017)

  6. Tripolitsiotis, A., Prokas, N., Kyritsis, S., Dollas, A., Papaefstathiou, I., Partsinevelos, P.: Dronesourcing: A Modular, Expandable Multi-Sensor UAV Platform for Combined. Real-Time Environmental Monitoring. Int. J. Remote Sens. 38, 2757–2770 (2017). https://doi.org/10.1080/01431161.2017.1287975

    Article  Google Scholar 

  7. Furukawa, T., Bourgault, F., Lavis, B., Durrant-Whyte, H.F.: Recursive Bayesian Search-and-Tracking Using Coordinated UAVs for Lost Targets. In: Proc. IEEE Int. Conf. Robot. Autom. pp. 2521–2526, Orlando (2006)

  8. Ha, I.-K., Cho, Y.-Z., Ha, I.-K., Cho, Y.-Z.: A Probabilistic Target Search Algorithm Based on Hierarchical Collaboration for Improving Rapidity of Drones. Sensors. 18, 2535 (2018). https://doi.org/10.3390/s18082535

    Article  Google Scholar 

  9. Lin, L., Goodrich, M.A.: Hierarchical Heuristic Search Using a Gaussian Mixture Model for UAV Coverage Planning. IEEE Trans. Cybern. 44, 2532–2544 (2014). https://doi.org/10.1109/TCYB.2014.2309898

    Article  Google Scholar 

  10. Brown, D., Sun, L.: Exhaustive Mobile Target Search and Non-Intrusive Reconnaissance Using Cooperative Unmanned Aerial Vehicles. In: Proc. Int. Conf. Unmanned Aircraft Syst. pp. 1425–1431, Miami (2017)

  11. Tang, Z., Ozguner, U.: On Non-Escape Search for a Moving Target by Multiple Mobile Sensor Agents. In: Proc. American Control Conf. pp. 3525–3530, Minneapolis (2006)

  12. Hayat, S., Yanmaz, E., Brown, T.X., Bettstetter, C.: Multi-Objective UAV Path Planning for Search and Rescue. In: Proc. IEEE Int. Conf. Robot. Autom. pp. 5569–5574, Singapore (2017)

  13. Pelosi, M., Brown, M.S.: Improved Search Paths for Camera-Equipped UAVS in Wilderness Search and Rescue. In: Proc. IEEE Symp. Series Comp. Intell. pp. 1–8, Honolulu (2017)

  14. Sun, J., Li, B., Jiang, Y., Wen, C.: A Camera-Based Target Detection and Positioning UAV System for Search and Rescue (SAR) Purposes. Sensors. 16, 1778 (2016). https://doi.org/10.3390/s16111778

    Article  Google Scholar 

  15. Dinnbier, N.M., Thueux, Y., Savvaris, A., Tsourdos, A.: Target Detection Using Gaussian Mixture Models and Fourier Transforms for UAV Maritime Search and Rescue. In: Proc. Int. Conf. Unmanned Aircraft Syst. pp. 1418–1424, Miami (2017)

  16. Goodrich, M.A., Morse, B.S., Gerhardt, D., Cooper, J.L., Quigley, M., Adams, J.A., Humphrey, C.: Supporting Wilderness Search and Rescue Using a Camera-Equipped Mini UAV. J. Field Robot. 25, 89–110 (2008). https://doi.org/10.1002/rob.20226

    Article  Google Scholar 

  17. Niedzielski, T., Jurecka, M., Miziński, B., Remisz, J., Ślopek, J., Spallek, W., Witek-Kasprzak, M., Kasprzak, Ł., Świerczyńska-Chlaściak, M.: A Real-Time Field Experiment on Search and Rescue Operations Assisted by Unmanned Aerial Vehicles. J. Field Robot. (2018). https://doi.org/10.1002/rob.21784

  18. Tomic, T., Schmid, K., Lutz, P., Domel, A., Kassecker, M., Mair, E., Grixa, I.L., Ruess, F., Suppa, M., Burschka, D.: Toward a Fully Autonomous UAV: Research Platform for Indoor and Outdoor Urban Search and Rescue. IEEE Robot. Autom. Mag. 19, 46–56 (2012). https://doi.org/10.1109/MRA.2012.2206473

    Article  Google Scholar 

  19. Perez-Grau, F.J., Ragel, R., Caballero, F., Viguria, A., Ollero, A.: Semi-Autonomous Teleoperation of UAVs in Search and Rescue Scenarios. In: Proc. Int. Conf. Unmanned Aircraft Syst. pp. 1066–1074, Miami (2017)

  20. Agcayazi, M.T., Cawi, E., Jurgenson, A., Ghassemi, P., Cook, G.: ResQuad: Toward a Semi-Autonomous Wilderness Search and Rescue Unmanned Aerial System. In: Proc. Int. Conf. Unmanned Aircraft Syst. pp. 898–904, Arlington, VA, USA (2016)

  21. Duan, H., Liu, S.: Unmanned Air/Ground Vehicles Heterogeneous Cooperative Techniques: Current Status and Prospects. Sci. China Technol. Sci. 53, 1349–1355 (2010). https://doi.org/10.1007/s11431-010-0122-4

    Article  Google Scholar 

  22. Caska, S., Gayretli, A.: A Survey of UAV/UGV Collaborative Systems. In: Proc. Int. Conf. Comput. Ind. Eng. Int. Symp. Intell. Manufacturing Service Systs. Joint Int. Symp. “Social Impacts Developments Information Manufacturing Service Syst.” pp. 453–463, Istanbul (2014)

  23. Delmerico, J., Mueggler, E., Nitsch, J., Scaramuzza, D.: Active Autonomous Aerial Exploration for Ground Robot Path Planning. IEEE Robot. Autom. Lett. 2, 664–671 (2017). https://doi.org/10.1109/LRA.2017.2651163

    Article  Google Scholar 

  24. Reardon, C., Fink, J.: Air-Ground Robot Team Surveillance of Complex 3D Environments. In: Proc. IEEE Int. Symp. Safety, Security, Rescue Robot. pp. 320–327, Lausanne (2016)

  25. Xiao, X., Dufek, J., Woodbury, T., Murphy, R.: UAV Assisted USV Visual Navigation for Marine Mass Casualty Incident Response. In: Proc. IEEE/RSJ Int. Conf. Intell. Robot. Syst. pp. 6105–6110, Vancouver (2017)

  26. Christie, G., Shoemaker, A., Kochersberger, K., Tokekar, P., McLean, L., Leonessa, A.: Radiation Search Operations Using Scene Understanding With Autonomous UAV and UGV. J. Field Robot. 34, 1450–1468 (2017). https://doi.org/10.1002/rob.21723

    Article  Google Scholar 

  27. Marconi, L., Melchiorri, C., Beetz, M., Pangercic, D., Siegwart, R., Leutenegger, S., Carloni, R., Stramigioli, S., Bruyninckx, H., Doherty, P., Kleiner, A., Lippiello, V., Finzi, A., Siciliano, B., Sala, A., Tomatis, N.: The SHERPA Project: Smart Collaboration Between Humans and Ground-Aerial Robots for Improving Rescuing Activities in Alpine Environments. In: Proc. IEEE Int. Symp. Safety, Security, Rescue Robot. pp. 1–4, College Station (2012)

  28. Qin, H., Meng, Z., Meng, W., Chen, X., Sun, H., Lin, F., Ang, M.H.: Autonomous Exploration and Mapping System Using Heterogeneous UAVs and UGVs in GPS-Denied Environments. IEEE Trans. Veh. Technol. 68, 1339–1350 (2019). https://doi.org/10.1109/TVT.2018.2890416

    Article  Google Scholar 

  29. Arbanas, B., Ivanovic, A., Car, M., Orsag, M., Petrovic, T., Bogdan, S.: Decentralized Planning and Control for UAV–UGV Cooperative Teams. Auton. Robot. (2018). https://doi.org/10.1007/s10514-018-9712-y

  30. Li, J., Deng, G., Luo, C., Lin, Q., Yan, Q., Ming, Z.: A Hybrid Path Planning Method in Unmanned Air/Ground Vehicle (UAV/UGV) Cooperative Systems. IEEE Trans. Veh. Technol. 65, 9585–9596 (2016). https://doi.org/10.1109/TVT.2016.2623666

    Article  Google Scholar 

  31. Minaeian, S., Liu, J., Son, Y.-J.: Vision-Based Target Detection and Localization via a Team of Cooperative UAV and UGVs. IEEE Trans. Syst. Man Cybern. Syst. 46, 1005–1016 (2016). https://doi.org/10.1109/TSMC.2015.2491878

    Article  Google Scholar 

  32. Manyam, S.G., Casbeer, D.W., Sundar, K.: Path Planning for Cooperative Routing of Air-Ground Vehicles. In: Proc. American Control Conf. pp. 4630–4635, Boston (2016)

  33. Tripathi, S.K., Sapre, R.M.: Robust Target Localization and Tracking Using Kalman Filtering for UGV-UAV Coordinated Operation. In: Proc. Int. Conf. Recent Advances Innovations Eng. pp. 1–6. IEEE, Jaipur (2016)

  34. Hood, S., Benson, K., Hamod, P., Madison, D., O’Kane, J.M., Rekleitis, I.: Bird’s Eye View: Cooperative Exploration by UGV and UAV. In: Proc. Int. Conf. Unmanned Aircraft Syst. pp. 247–255. IEEE, Miami (2017)

  35. Rosa, L., Cognetti, M., Nicastro, A., Alvarez, P., Oriolo, G.: Multi-task Cooperative Control in a Heterogeneous Ground-Air Robot Team. IFAC-Pap. 48, 53–58 (2015). https://doi.org/10.1016/j.ifacol.2015.06.463

    Article  Google Scholar 

  36. Lum, C.W., Vagners, J., Rysdyk, R.T.: Search Algorithm for Teams of Heterogeneous Agents With Coverage Guarantees. J. Aerosp. Comput. Inf. Commun. 7, 1–31 (2010). https://doi.org/10.2514/1.44088

    Article  Google Scholar 

  37. Sauter, J.A., Mathews, R.S., Yinger, A., Robinson, J.S., Moody, J., Riddle, S.: Distributed Pheromone-Based Swarming Control of Unmanned Air and Ground Vehicles for RSTA. In: Unmanned Systems Technology X. p. 69620C. International Society for Optics and Photonics (2008)

  38. Grocholsky, B., Keller, J., Kumar, V., Pappas, G.: Cooperative Air and Ground Surveillance. IEEE Robot. Autom. Mag. 13, 16–25 (2006). https://doi.org/10.1109/MRA.2006.1678135

    Article  Google Scholar 

  39. Beck, Z., Teacy, L., Rogers, A., Jennings, N.R.: Online Planning for Collaborative Search and Rescue by Heterogeneous Robot Teams. In: Proc. Int. Conf. Autonomous Agents Multiagent Syst. pp. 1024–1033. International Foundation for Autonomous Agents and Multiagent Systems, Singapore (2016)

  40. Pippin, C.E., Christensen, H.: A Bayesian Formulation for Auction-Based Task Allocation in Heterogeneous Multi-Agent Teams. In: Proc. Ground/Air Multisensor Interoperability, Integration, Networking Persistent ISR II. p. 804710. International Society for Optics and Photonics, Orlando (2011)

  41. Fregene, K., Kennedy, D.C., Wang, D.W.L.: Toward a Systems- and Control-Oriented Agent Framework. IEEE Trans. Syst. Man Cybern. Part B Cybern. 35, 999–1012 (2005). https://doi.org/10.1109/TSMCB.2005.848491

    Article  Google Scholar 

  42. Flushing, E.F., Kudelski, M., Gambardella, L.M., Caro, G.A.D.: Connectivity-Aware Planning of Search and Rescue Missions. In: Proc. IEEE Int. Symp. Safety, Security, Rescue Robot. pp. 1–8, Linkoping (2013)

  43. Yu, H., Meier, K., Argyle, M., Beard, R.W.: Cooperative Path Planning for Target Tracking in Urban Environments Using Unmanned Air and Ground Vehicles. IEEEASME Trans. Mechatron. 20, 541–552 (2015). https://doi.org/10.1109/TMECH.2014.2301459

    Article  Google Scholar 

  44. Macwan, A., Nejat, G., Benhabib, B.: Target-Motion Prediction for Robotic Search and Rescue in Wilderness Environments. IEEE Trans. Syst. Man Cybern. Part B Cybern. 41, 1287–1298 (2011). https://doi.org/10.1109/TSMCB.2011.2132716

    Article  Google Scholar 

  45. Kashino, Z., Nejat, G., Benhabib, B.: Multi-UAV based Autonomous Wilderness Search and Rescue using Target Iso-Probability Curves. In: Proc. Int. Conf. Unmanned Aircraft Syst. pp. 628–635, Atlanta (2019)

  46. Macwan, A., Vilela, J., Nejat, G., Benhabib, B.: A Multirobot Path-Planning Strategy for Autonomous Wilderness Search and Rescue. IEEE Trans. Cybern. 45, 1784–1797 (2015). https://doi.org/10.1109/TCYB.2014.2360368

    Article  Google Scholar 

  47. Doherty, P.J., Guo, Q., Doke, J., Ferguson, D.: An Analysis of Probability of Area Techniques for Missing Persons in Yosemite National Park. Appl. Geogr. 47, 99–110 (2014). https://doi.org/10.1016/j.apgeog.2013.11.001

    Article  Google Scholar 

  48. Kashino, Z., Kim, J.Y., Nejat, G., Benhabib, B.: Spatiotemporal Adaptive Optimization of a Static-Sensor Network via a Non-Parametric Estimation of Target Location Likelihood. IEEE Sensors J. 17, 1479–1492 (2017). https://doi.org/10.1109/JSEN.2016.2638623

    Article  Google Scholar 

  49. Lin, L., Goodrich, M.A.: A Bayesian Approach to Modeling Lost Person Behaviors Based on Terrain Features in Wilderness Search and Rescue. Comput. Math. Organ. Theory. 16, 300–323 (2010). https://doi.org/10.1007/s10588-010-9066-2

    Article  Google Scholar 

  50. Mohibullah, W., Julier, S.J.: Stigmergic Search for a Lost Target in Wilderness. In: Proc. Sensor Signal Processing Defence. pp. 1–5, London (2011)

  51. Sava, E., Twardy, C., Koester, R., Sonwalkar, M.: Evaluating Lost Person Behavior Models. Trans. GIS. 20, 38–53 (2016). https://doi.org/10.1111/tgis.12143

    Article  Google Scholar 

  52. Koester, R.J.: Lost Person Behavior: A Search and Rescue Guide on Where to Look for Land. Air and Water. dbS Productions, Charlottesville (2008)

    Google Scholar 

  53. Croft, E.A., Benhabib, B., Fenton, R.G.: Near-time optimal robot motion planning for on-line applications. J. Robot. Syst. 12, 553–567 (1995). https://doi.org/10.1002/rob.4620120805

    Article  MATH  Google Scholar 

  54. Macwan, A., Nejat, G., Benhabib, B.: Optimal Deployment of Robotic Teams for Autonomous Wilderness Search and Rescue. In: Proc. IEEE/RSJ Int. Conf. Intell. Robot. Syst. pp. 4544–4549, San Francisco (2011)

  55. Tobler, W.: Non-Isotropic Geographic Modeling. Three Present. Geogr. Anal. Model. St. Barbara Natl. Cent. Geogr. Inf. Anal. Univ. Calif. (1993)

  56. Bakhtari, A., Naish, M.D., Eskandari, M., Croft, E.A., Benhabib, B.: Active-Vision-Based Multisensor Surveillance – An Implementation. IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 36, 668–680 (2006). https://doi.org/10.1109/TSMCC.2005.855525

    Article  Google Scholar 

  57. Bakhtari, A., Benhabib, B.: An Active Vision System for Multitarget Surveillance in Dynamic Environments. IEEE Trans. Syst. Man Cybern. Part B Cybern. 37, 190–198 (2007). https://doi.org/10.1109/TSMCB.2006.883423

    Article  Google Scholar 

  58. Shneydor, N.A.: Missile Guidance and Pursuit: Kinematics, Dynamics and Control. Woodhead Publishing (1998)

  59. Borg, J.M., Mehrandezh, M., Fenton, R.G., Benhabib, B.: Navigation-Guidance-Based Robotic Interception of Moving Objects in Industrial Settings. J. Intell. Robot. Syst. 33, 1–23 (2002). https://doi.org/10.1023/A:1014490704273

    Article  MATH  Google Scholar 

  60. Kunwar, F., Benhabib, B.: Rendezvous-Guidance Trajectory Planning for Robotic Dynamic Obstacle Avoidance and Interception. IEEE Trans. Syst. Man Cybern. Part B Cybern. 36, 1432–1441 (2006). https://doi.org/10.1109/TSMCB.2006.877792

    Article  Google Scholar 

  61. Kunwar, F., Wong, F., Mrad, R.B., Benhabib, B.: Guidance-Based On-Line Robot Motion Planning for the Interception of Mobile Targets in Dynamic Environments. J. Intell. Robot. Syst. 47, 341–360 (2006). https://doi.org/10.1007/s10846-006-9080-2

    Article  Google Scholar 

  62. Hujic, D., Croft, E.A., Zak, G., Fenton, R.G., Mills, J.K., Benhabib, B.: The robotic interception of moving objects in industrial settings: strategy development and experiment. IEEEASME Trans. Mechatron. 3, 225–239 (1998). https://doi.org/10.1109/3516.712119

    Article  Google Scholar 

  63. Rossi, R.J.: Mathematical Statistics: An Introduction to Likelihood Based Inference. Wiley, Hoboken (2018)

    Book  Google Scholar 

  64. Julier, S.J., Uhlmann, J.K.: Unscented Filtering and Nonlinear Estimation. Proc. IEEE. 92, 401–422 (2004). https://doi.org/10.1109/JPROC.2003.823141

    Article  Google Scholar 

  65. Search Experiment Example for Aerial Wilderness Search and Rescue with Ground Support, https://www.youtube.com/watch?v=bX0IAm-fRJs

  66. Zhao, Q., Zhang, L., Han, Y., Fan, C.: Polishing Path Generation for Physical Uniform Coverage of the Aspheric Surface Based on the Archimedes Spiral in Bonnet Polishing. Proc. Inst. Mech. Eng. Part B J. Eng. Manuf. 0954405419838655 (2019). https://doi.org/10.1177/0954405419838655

Download references

Acknowledgements

The authors would like to acknowledge the support received, in part, by the Natural Sciences and Engineering Research Council of Canada (NSERC).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Beno Benhabib.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kashino, Z., Nejat, G. & Benhabib, B. Aerial Wilderness Search and Rescue with Ground Support. J Intell Robot Syst 99, 147–163 (2020). https://doi.org/10.1007/s10846-019-01105-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10846-019-01105-y

Keywords

Navigation