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Decentralized planning and control for UAV–UGV cooperative teams

  • Barbara Arbanas
  • Antun Ivanovic
  • Marko Car
  • Matko Orsag
  • Tamara Petrovic
  • Stjepan Bogdan
Article
Part of the following topical collections:
  1. Special Issue on Distributed Robotics: From Fundamentals to Applications

Abstract

In this paper we study a symbiotic aerial vehicle-ground vehicle robotic team where unmanned aerial vehicles (UAVs) are used for aerial manipulation tasks, while unmanned ground vehicles (UGVs) aid and assist them. UGV can provide a UAV with a safe landing area and transport it across large distances, while UAV can provide an additional degree of freedom for the UGV, enabling it to negotiate obstacles. We propose an overall system control framework that includes high-accuracy motion planning for each individual robot and ad-hoc decentralized mission planning for complex missions. Experimental results obtained in a mockup arena for parcel transportation scenario show that the system is able to plan and execute missions in various environments and that the obtained plans result in lower energy consumption.

Keywords

Unmanned aerial system Aerial manipulation Heterogeneous robotics systems Decentralized planning 

Notes

Acknowledgements

This paper was supported by the EU-FP7-ICT project European Robotics Challenges (EuRoC), Grant Agreement No. 608849.

Supplementary material

Supplementary material 1 (mp4 286176 KB)

References

  1. Amato, C., Konidaris, G., Cruz, G., Maynor, C. A., How, J. P., & Kaelbling, L. P. (2015). Planning for decentralized control of multiple robots under uncertainty. In: IEEE International Conference on Robotics and Automation (ICRA) (pp. 1241–1248).Google Scholar
  2. Arbanas, B., Ivanovic, A., Car, M., Haus, T., Orsag, M., Petrovic, T., & Bogdan, S. (2016) Aerial-ground robotic system for autonomous delivery tasks. In: IEEE International Conference on Robotics and Automation (ICRA) (pp. 5463–5468).Google Scholar
  3. Bradski, D. G. R., & Kaehler, A. (2008). Learning Opencv (1st ed.). Sebastopol: O’Reilly Media Inc.Google Scholar
  4. Butzke, J., Gochev, K., Holden, B., Jung, E. J., & Likhachev, M. (2016). Planning for a ground-air robotic system with collaborative localization. In: IEEE International conference on robotics and automation (ICRA) (pp 284–291).Google Scholar
  5. Cirillo, M., Pecora, F., Andreasson, H., Uras, T., & Koenig, S. (2014). Integrated motion planning and coordination for industrial vehicles. In: Proceedings of the 24th international conference on international conference on automated planning and scheduling (pp. 463–471).Google Scholar
  6. Cvisic, I., & Petrovic, I. (2015). Stereo odometry based on careful feature selection and tracking. In: European conference on mobile robots (ECMR) (pp. 1–6).Google Scholar
  7. Cvisic, I., Cesic, J., Markovic, I., & Petrovic, I. (2017). Soft-SLAM: Computationally efficient stereo visual SLAM for autonomous UAVS. Journal of Field Robotics.Google Scholar
  8. Decker, K. S., & Lesser, V. R. (1995). Designing a family of coordination algorithms. In Proceedings of the 1st international conference on multi-agent systems (ICMAS-95) (pp. 73–80).Google Scholar
  9. Di Paola, D., Gasparri, A., Naso, D., & Lewis, F. L. (2015). Decentralized dynamic task planning for heterogeneous robotic networks. Autonomous Robots, 38(1), 31–48.CrossRefGoogle Scholar
  10. Dias, A., Capitan, J., Merino, L., Almeida, J., Lima, P., & Silva, E. (2015). Decentralized target tracking based on multi-robot cooperative triangulation. In IEEE International Conference on Robotics and Automation (ICRA) (pp. 3449–3455). IEEE.Google Scholar
  11. Ding, X. C., Kloetzer, M., Chen, Y., & Belta, C. (2011). Automatic deployment of robotic teams. IEEE Robotics Automation Magazine, 18(3), 75–86.CrossRefGoogle Scholar
  12. Drenner, A., Janssen, M., Carlson, C., & Papanikolopoulos, N. (2007). Design, control, and simulation of marsupial systems for extending operational lifetime. In European Control Conference (ECC) (pp. 3146–3152).Google Scholar
  13. Fumagalli, M., Naldi, R., Macchelli, A., Carloni, R., Stramigioli, S., & Marconi, L. (2012). Modeling and control of a flying robot for contact inspection. In IEEE/RSJ international conference on intelligent robots and systems (IROS) (pp. 3532–3537).Google Scholar
  14. Fumagalli, M., Naldi, R., Macchelli, A., Forte, F., Keemink, A., Stramigioli, S., et al. (2014). Developing an aerial manipulator prototype: Physical interaction with the environment. IEEE Robotics Automation Magazine, 21(3), 41–50.CrossRefGoogle Scholar
  15. Gerkey, B. P., & Mataric, M. J. (2002). Sold!: Auction methods for multirobot coordination. IEEE Transactions on Robotics and Automation, 18(5), 758–768.CrossRefGoogle Scholar
  16. Gonzalez, R. C., & Woods, R. E. (2006). Digital image processing (3rd ed.). Upper Saddle River, NJ: Prentice-Hall Inc.Google Scholar
  17. Guo, M., Tumova, J., & Dimarogonas, D.V. (2014). Cooperative decentralized multi-agent control under local LTL tasks and connectivity constraints. In: 53rd IEEE conference on decision and control (pp. 75–80).Google Scholar
  18. Horling, B., Lesser, V., Vincent, R., Wagner, T., Raja, A., Zhang, S., Decker, K., & Garvey, A. (1999). The TAEMS white paper.Google Scholar
  19. Hornung, A., Wurm, K. M., Bennewitz, M., Stachniss, C., & Burgard, W. (2013). OctoMap: An efficient probabilistic 3D mapping framework based on octrees. Autonomous Robots, 34, 189–206.CrossRefGoogle Scholar
  20. Hsieh, M. A., Cowley, A., Keller, J. F., Chaimowicz, L., Grocholsky, B., Kumar, V., et al. (2007). Adaptive teams of autonomous aerial and ground robots for situational awareness. Journal of Field Robotics, 24(11–12), 991–1014.CrossRefGoogle Scholar
  21. Jimenez-Cano, A., Martin, J., Heredia, G., Ollero, A., & Cano, R. (2013). Control of an aerial robot with multi-link arm for assembly tasks. In: IEEE international conference on robotics and automation (ICRA) (pp. 4916–4921).Google Scholar
  22. Kim, S., Choi, S., & Kim, H.J. (2013). Aerial manipulation using a quadrotor with a two dof robotic arm. In IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 4990–4995).Google Scholar
  23. Kondak, K., Huber, F., Schwarzbach, M., Laiacker, M., Sommer, D., Bejar, M., & Ollero, A. (2014). Aerial manipulation robot composed of an autonomous helicopter and a 7 degrees of freedom industrial manipulator. In IEEE international conference on robotics and automation (ICRA) (pp. 2107–2112). IEEE.Google Scholar
  24. Korchenko, A., & Illyash, O. (2013). The generalized classification of unmanned air vehicles. In: Actual problems of unmanned air vehicles developments proceedings (APUAVD) (pp. 28–34). IEEE.Google Scholar
  25. Korpela, C., Orsag, M., Pekala, M., & Oh, P. (2013). Dynamic stability of a mobile manipulating unmanned aerial vehicle. In IEEE ICRA (pp. 4922–4927).Google Scholar
  26. Korpela, C., Orsag, M., & Oh, P. (2014). Towards valve turning using a dual-arm aerial manipulator. In IEEE/RSJ international conference on intelligent robots and systems (IROS 2014) (pp. 3411–3416). IEEE.Google Scholar
  27. Krnjak, A., Draganjac, I., Bogdan, S., Petrovic, T., Miklic, D., & Kovacic, Z. (2015). Decentralized control of free ranging AGVS in warehouse environments. In IEEE international conference on robotics and automation (ICRA) (pp. 2034–2041).Google Scholar
  28. LARICSlab. (2017a). https://goo.gl/0J1hmK.
  29. LARICSlab. (2017b). https://goo.gl/cZMrHQ.
  30. Lemaire, T., Alami, R., & Lacroix, S. (2004). A distributed tasks allocation scheme in multi-uav context. In: Proceedings of the ICRA’04 IEEE international conference on robotics and automation, 2004 (Vol. 4, pp 3622–3627).Google Scholar
  31. Lesser, V., Decker, K., Wagner, T., Carver, N., Garvey, A., Horling, B., et al. (2004). Evolution of the GPGP/TÆMS domain-independent coordination framework. Autonomous Agents and Multi-Agent Systems, 9(1–2), 87–143.CrossRefGoogle Scholar
  32. Lindsey, Q., Mellinger, D., & Kumar, V. (2012). Construction with quadrotor teams. Autonomous Robots, 33(3), 323–336.CrossRefGoogle Scholar
  33. Maini, P., & Sujit, P. (2015). On cooperation between a fuel constrained UAV and a refueling UGV for large scale mapping applications. In International conference on unmanned aircraft systems (ICUAS) (pp. 1370–1377). IEEE.Google Scholar
  34. Mathew, N., Smith, S. L., & Waslander, S. L. (2015). Planning paths for package delivery in heterogeneous multirobot teams. IEEE Transactions on Automation Science and Engineering, 12(4), 1298–1308.CrossRefGoogle Scholar
  35. Michael, N., Shen, S., Mohta, K., Mulgaonkar, Y., Kumar, V., Nagatani, K., et al. (2012). Collaborative mapping of an earthquake-damaged building via ground and aerial robots. Journal of Field Robotics, 29(5), 832–841.CrossRefGoogle Scholar
  36. Miskovic, N., Bogdan, S., Nad, E., Mandic, F., Orsag, M., & Haus, T. (2014). Unmanned marsupial sea-air system for object recovery. In 22nd Mediterranean Conference of Control and Automation (MED) (pp. 740–745).Google Scholar
  37. Moré, J. J. (1978). The Levenberg-Marquardt algorithm: Implementation and theory. In G. A. Watson (Ed.), Numerical analysis. Lecture notes in mathematics (Vol. 630, pp. 105–116). Berlin, Heidelberg: Springer.Google Scholar
  38. Omidshafiei, S., Agha-Mohammadi, A. A., Amato, C., & How, J. P. (2015). Decentralized control of partially observable markov decision processes using belief space macro-actions. In IEEE International Conference on Robotics and Automation (ICRA) (pp. 5962–5969).Google Scholar
  39. Orsag, M., Korpela, C., Bogdan, S., & Oh, P. (2014). Hybrid adaptive control for aerial manipulation. Journal of Intelligent and Robotic Systems, 73(1–4), 693–707.CrossRefGoogle Scholar
  40. Papachristos, C., Tzes, A. (2014). The power-tethered UAV-UGV team: A collaborative strategy for navigation in partially-mapped environments. In Mediterranean conference on control and automation (pp. 1153–1158).Google Scholar
  41. Petrovic, T., Haus, T., Arbanas, B., Orsag, M., & Bogdan, S. (2015). Can UAV and UGV be best buddies? Towards heterogeneous aerial-ground cooperative robot system for complex aerial manipulation tasks. In: 12th International conference on informatics in control, automation and robotics (ICINCO) (Vol. 01, pp. 238–245).Google Scholar
  42. Pimentel, B.S., Campos, M.F.M. (2003). Cooperative communication in ad hoc networked mobile robots. In Proceedings of the IEEE/RSJ international conference on intelligent robots and systems (IROS 2003) (Cat. No. 03CH37453) (Vol. 3, pp. 2876–2881).Google Scholar
  43. Raman, V. (2014). Reactive switching protocols for multi-robot high-level tasks. In IEEE/RSJ international conference on intelligent robots and systems (IROS 2014) (pp. 336–341).Google Scholar
  44. Saribatur, Z., Erdem, E., & Patoglu, V. (2014). Cognitive factories with multiple teams of heterogeneous robots: Hybrid reasoning for optimal feasible global plans. In IEEE/RSJ International conference on intelligent robots and systems (IROS 2014) (pp. 2923–2930).Google Scholar
  45. Scholten, J., Fumagalli, M., Stramigioli, S., & Carloni, R. (2013). Interaction control of an uav endowed with a manipulator. In IEEE International conference on robotics and automation (ICRA) (pp. 4910–4915)Google Scholar
  46. Siltanen, S. (2012). Theory and applications of marker-based augmented reality. VTT Science.Google Scholar
  47. Sreenath, K., Michael, N., Kumar, V. (2013). Trajectory generation and control of a quadrotor with a cable-suspended load-a differentially-flat hybrid system. In IEEE ICRA (pp. 4888–4895). IEEE.Google Scholar
  48. Stentz, A., & Dias, M. B. (1999). A free market architecture for coordinating multiple robots. DTIC Document: Tech. rep.Google Scholar
  49. Şucan, I.A., Moll, M., Kavraki, L. E. (2012). The open motion planning library. IEEE Robotics & Automation Magazine, 19(4), 72–82. http://ompl.kavrakilab.org.
  50. Tang, F., Parker, L.E. (2005). Asymtre: Automated synthesis of multi-robot task solutions through software reconfiguration. In Proceedings of the IEEE International Conference on Robotics and Automation (pp. 1501–1508).Google Scholar
  51. Thomas, J., Loianno, G., Sreenath, K., Kumar, V. (2014). Toward image based visual servoing for aerial grasping and perching. In IEEE ICRA (pp. 2113–2118).Google Scholar
  52. Wurm, K., Dornhege, C., Nebel, B., Burgard, W., & Stachniss, C. (2013). Coordinating heterogeneous teams of robots using temporal symbolic planning. Autonomous Robots, 34(4), 277–294.CrossRefGoogle Scholar
  53. Yan, Z., Jouandeau, N., & Cherif, A. A. (2013). A survey and analysis of multi-robot coordination. International Journal of Advanced Robotic Systems, 10(12), 399.CrossRefGoogle Scholar
  54. Zikou, L., Papachristos, C., Alexis, K., & Tzes, A. (2015). Inspection operations using an aerial robot powered-over-tether by a ground vehicle. In International symposium on visual computing (pp. 455–465).Google Scholar
  55. Zlot, R., & Stentz, A. (2006). Market-based multirobot coordination for complex tasks. The International Journal of Robotics Research, 25(1), 73–101.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Laboratory for Robotics and Intelligent Control Systems (LARICS), Faculty of Electrical Engineering and Computing, Unska 3ZagrebCroatia

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