Skip to main content

Collaborative ground and aerial robots in hazard mapping based on heterogeneous coverage

Abstract

A collaborative scheme of multiple ground and aerial robots applying a heterogeneous coverage control approach is presented. It aims to provide a density map of a contaminated area from hazardous material. Compared to a homogeneous scheme, heterogeneity enhances the coverage level by minimizing error and variance due to the estimation process. In this scheme, a weighting formulation based on the different characteristics of ground and aerial robots is formalized. The contaminated area is partitioned unequally according to the number of deployed robots corresponding to the robot’s weight and type. It shows better estimation values of the estimated density distribution map than the homogeneous scheme. The operation time needed to provide an estimation map of density distribution over the region is also faster than the homogeneous scheme.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Availability of data and materials

Not applicable.

References

  • Butzkey, J., Dornbushy, A., Likhachevy, M.: 3-D exploration with an air-ground robotic system. In: 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 28 September 2015–02 October 2015, Hamburg, Germany, IEEE, pp 3241–3248 (2015). https://doi.org/10.1109/IROS.2015.7353827

  • Cantelli, L., Presti, M., Mangiameli, M.L., Melita, C.D., Muscato, G.: Autonomous cooperation between UAV and UGV to improve navigation and environmental monitoring in rough environments. In: 10th International symposium Humanitarian Demining (HUDEM), pp 2005–2008 (2013). https://www.researchgate.net/publication/303245963_Autonomous_Cooperation_between_UAV_and_UGV_to_improve_navigation_and_environmental_monitoring_in_rough_environments

  • Carron, A., Todescato, M., Carli, R., Schenato, L., Pillonetto, G.: Multi-agents adaptive estimation and coverage control using Gaussian regression. In: European Control Conference (ECC), 15–17 July 2015. Linz, Austria, IEEE (2015)

  • Chen, J., Zhang, X., Xin, B., Fang, H.: Coordination between unmanned aerial and ground vehicles: a taxonomy and optimization perspective. IEEE Trans. Cybern. 46(4), 959–972 (2016). https://doi.org/10.1109/TCYB.2015.2418337

    Article  Google Scholar 

  • Cook, Z., Kazemeini, M., Barzilov, A., Yim, W.: Low altitude contour mapping of radiation fields using UAS swarm. Intell. Serv. Robot. 12, 219–230 (2019). https://doi.org/10.1007/s11370-019-00277-8

    Article  Google Scholar 

  • Cortes, J.: Coverage optimization and spatial load balancing by robotic sensor networks. IEEE Trans. Autom. Control 55(3), 749–754 (2010). https://doi.org/10.1109/TAC.2010.2040495

    Article  MathSciNet  MATH  Google Scholar 

  • Cortés, J., Martínez, S., Karatas, T., Bullo, F., Member, S.: Coverage control for mobile sensing networks. In: Proceedings 2002 IEEE International Conference on Robotics and Automation, 11–15 May 2002, Washington, DC, USA, IEEE, vol 4, pp 243–255 (2002). https://doi.org/10.1109/ROBOT.2002.1014727

  • Furrer, F., Burri, M., Achtelik, M., Siegwart, S.: Robot Operating System (ROS): The Complete Reference, vol 1, pp 595–625. Springer (2016)

  • Han, J., Chen, Y.: Multiple UAV formations for cooperative source seeking and contour mapping of a radiative signal field. J. Intell. Robot. Syst. 74, 323–332 (2014). https://doi.org/10.1007/s10846-013-9897-4

    Article  Google Scholar 

  • Kohlbrecher, S.: Hector open source modules for autonomous mapping and navigation with rescue robots. In: and others (ed) RoboCup 2013: RoboCup 2013: Robot World Cup XVII, Springer, Lecture Notes in Computer Science, vol 8371, pp 624–631 (2014). https://doi.org/10.1007/978-3-662-44468-9

  • Lazna, T., Gabrlik, P., Jilek, T., Zalud, L.: Cooperation between an unmanned aerial vehicle and an unmanned ground vehicle in highly accurate localization of gamma radiation hotspots. Int. J. Adv. Robot. Syst. 15, 1–16 (2018). https://doi.org/10.1177/1729881417750787

    Article  Google Scholar 

  • Li, W., Cassandras, C.G.: Distributed cooperative coverage control of sensor networks. In: Proceedings of the 44th IEEE Conference on Decision and Control, 12-15 December 2005, Seville, Spain, IEEE, pp 2542–2547 (2006). https://doi.org/10.1109/CDC.2005.1582545

  • Meyer, J., Sendobry, A., Kohlbrecher, S., Klingauf, U.: Comprehensive simulation of quadrotor UAVs using ROS and Gazebo. In: International Conference on Simulation, Modeling, and Programming for Autonomous Robots, 5-8 November 2012, Tsukuba, Japan, Springer, Lecture Notes in Computer Science, vol 7628, pp 400–411 (2012). https://doi.org/10.1007/978-3-642-34327-8_36

  • Owen, M., Yu, H., Mclain, T., Beard, R.: Moving ground target tracking in urban terrain using air/ground vehicles. In: 2010 IEEE Globecom Workshops, 06–10 December 2010, Miami, FL, USA, IEEE, vol 10, pp 1816–1820 (2011). https://doi.org/10.1109/GLOCOMW.2010.5700254

  • Pierson, A., Schwager, M.: Adaptive inter-robot trust for robust multi-robot sensor coverage. In: the 16th International Symposium of Robotics Research, 16–19 December 2013, Singapore, Springer, Springer Tracts in Advanced Robotics, vol 114, pp 167–183 (2016). https://doi.org/10.1007/978-3-319-28872-7_10

  • Pierson, A., Figueiredo, L.C., Pimenta, L.C.A., Schwager, M.: Adapting to performance variations in multi-robot coverage. In: 2015 IEEE International Conference on Robotics and Automation (ICRA), 26–30 May 2015, Seattle, WA, USA, IEEE, pp 415–420 (2015). https://doi.org/10.1109/ICRA.2015.7139032

  • Pierson, A., Figueiredo, L.C., Pimenta, L.C.A., Schwager, M.: Adapting to sensing and actuation variations in multi-robot coverage. Int. J. Robot. Res. 36(3), 337–354 (2017). https://doi.org/10.1177/0278364916688103

    Article  Google Scholar 

  • Pimenta, L.C.A., Kumar, V., Mesquita, R.C., Pereira, G.A.S.: Sensing and coverage for a network of heterogeneous robots. In: 2008 47th IEEE Conference on Decision and Control, 09–11 December 2008, Cancun, Mexico, IEEE, pp 3947–3952 (2009). https://doi.org/10.1109/CDC.2008.4739194

  • Pinkam, N., Jeong, S., Chong, N.Y.: Exploration of a group of mobile robots for multiple radiation sources estimation. In: 2016 IEEE International Symposium on Robotics and Intelligent Sensors (IRIS), 17–20 December 2016, Tokyo, Japan, IEEE, pp 199–206 (2017). https://doi.org/10.1109/IRIS.2016.8066091

  • Pinkam, N., Al, A., Newaz, R., Jeong, S., Young, N.: Rapid coverage of regions of interest for environmental monitoring. Intell. Serv. Robot. 12, 393–406 (2019). https://doi.org/10.1007/s11370-019-00290-x

    Article  Google Scholar 

  • Prabowo, Y.A., Trilaksono, B.R.: Collision-free coverage control of swarm robotics based on Gaussian process regression to estimate sensory function in non-convex environment. Int. J. Electr. Eng. Inform. 11(1), 125–143 (2019). https://doi.org/10.15676/ijeei.2019.11.1.8

    Article  Google Scholar 

  • Schwager, M., Slotine, J.J., Rus, D.: Decentralized, adaptive coverage control for networked robots. Int. J. Robot. Res. 28(3), 357–375 (2009). https://doi.org/10.1177/0278364908100177

    Article  Google Scholar 

  • Shi, Y., Wang, N., Zheng, J., Zhang, Y., Yi, S., Luo, W., Sycara, K.: Adaptive informative sampling with environment partitioning for heterogeneous multi-robot systems. In: 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 24 October 2020–24 January 2021, Las Vegas, NV, USA, IEEE (2021). https://doi.org/10.1109/IROS45743.2020.9341711

  • Todescato, M., Carron, A., Carli, R., Pillonetto, G., Schenato, L.: Multi-robots Gaussian estimation and coverage control: From client-server to peer-to-peer architectures. Automatica 80, 284–294 (2017). https://doi.org/10.1016/j.automatica.2017.02.045

    Article  MathSciNet  MATH  Google Scholar 

  • Wang, J., Wang, C., Xin, M., Ding, Z., Shan, J.: Optimal coverage control of multi-robot systems. In: Zhu QM (ed) Cooperative Control of Multi-Agent Systems. Academic Press, pp 123–132 (2020). https://doi.org/10.1016/C2019-0-01681-0

Download references

Acknowledgements

We sincerely thank the Endowment Fund of Education, Ministry of Finance, the Republic of Indonesia (LPDP RI), for partially funding this research and financial support of the doctoral study through the BUDI-DN scholarship (Grant Number: 201812210113689). We also thank Telkom University, the first author’s home base institution, for supporting the doctoral study.

Funding

The Endowment Fund of Education partially funded this research, Ministry of Finance, the Republic of Indonesia (LPDP RI), supporting doctoral scholarship (BUDI-DN, Grant Number: 201812210113689).

Author information

Authors and Affiliations

Authors

Contributions

All authors contributed to the study’s conception and design. ANJ wrote material preparation, data collection, analysis, and manuscript. Meanwhile, other authors directed and supervised the research; reviewed, commented, and corrected previous manuscript versions. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Agung Nugroho Jati.

Ethics declarations

Conflict of interest

The authors declare no conflict of interest.

Additional information

Publisher's Note

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

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jati, A.N., Trilaksono, B.R., Hidayat, E.M.I. et al. Collaborative ground and aerial robots in hazard mapping based on heterogeneous coverage. Int J Intell Robot Appl 7, 615–630 (2023). https://doi.org/10.1007/s41315-023-00288-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s41315-023-00288-w

Keywords