Hostname: page-component-586b7cd67f-gb8f7 Total loading time: 0 Render date: 2024-11-25T22:56:23.320Z Has data issue: false hasContentIssue false
  • English
  • Français

Distributed cooperative deployment of heterogeneous autonomous agents: a Pareto suboptimal approach

Published online by Cambridge University Press:  30 August 2018

Giovanni Franzini Open the ORCID record for Giovanni Franzini [Opens in a new window]  and
Mario Innocenti
Giovanni Franzini*
Affiliation:
Department of Information Engineering, University of Pisa, Largo Lucio Lazzarino 1, Pisa 56122, Italy. E-mail: [email protected]
Mario Innocenti
Affiliation:
Department of Information Engineering, University of Pisa, Largo Lucio Lazzarino 1, Pisa 56122, Italy. E-mail: [email protected]
*
*Corresponding author. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Summary

The paper presents a distributed cooperative control law for autonomous deployment of a team of heterogeneous agents. Deployment problems deal with the coordination of groups of agents in order to cover one or more assigned areas of the operational space. In particular, we consider a team composed by agents with different dynamics, sensing capabilities, and resources available for the deployment. Sensing heterogeneity is addressed by means of the descriptor function framework, an abstraction that provides a set of mathematical tools for describing both agent sensing capabilities and the desired deployment. A distributed cooperative control law is then formally derived finding a suboptimal solution of a cooperative differential game, where the agents are interested in achieving the requested deployment, while optimizing the resources usage according to their dynamics. The control law effectiveness is proven by theoretical arguments, and supported by numerical simulations.

Keywords

Heterogeneous autonomous agentsCooperative controlDistributed controlDeployment problems
Type
Articles
Information
Robotica , Volume 36 , Issue 12 , December 2018 , pp. 1943 - 1962
Copyright
Copyright © Cambridge University Press 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Bullo, F., Cortés, J. and Martínez, S., Distributed Control of Robotic Networks (Princeton University Press, Princeton, New Jersey, USA, 2009).Google Scholar
2. Cortés, J., Martínez, S., Karatas, T. and Bullo, F., “Coverage control for mobile sensing networks,” IEEE Trans. Robot. Autom. 20 (2), 243–255 (2004). https://doi.org/10.1109/TRA.2004.824698.Google Scholar
3. Wang, X., Han, S., Wu, Y. and Wang, X., “Coverage and energy consumption control in mobile heterogeneous wireless sensor networks,” IEEE Trans. Autom. Control 58 (4), 975–988 (2013). https://doi.org/10.1109/TAC.2012.2225511.Google Scholar
4. Carpin, S., Chung, T. H. and Sadler, B. M., “Theoretical Foundations of High-Speed Robot Team Deployment,” Proceedings of the IEEE International Conference on Robotics and Automation, Karlsruhe, Germany (2013) pp. 2033–2040. https://doi.org/10.1109/ICRA.2013.6630849.Google Scholar
5. Dunbabin, M. and Marques, L., “Robots for environmental monitoring: Significant advancements and applications,” IEEE Robot. Autom. Mag. 19 (1), 24–39 (2012). https://doi.org/10.1109/MRA.2011.2181683.Google Scholar
6. Albani, D., Nardi, D. and Trianni, V., “Field Coverage and Weed Mapping by UAV Swarms,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (Sep. 2017) pp. 4319–4325. https://doi.org/10.1109/IROS.2017.8206296.Google Scholar
7. Wang, Z.-J. and Li, W., “A solution to cooperative area coverage surveillance for a swarm of MAVs,” Int. J. Adv. Robot. Syst. 10 (12) (2013) pp. 398(1)–398(8). https://doi.org/10.5772/56801.Google Scholar
8. Saeed, A., Abdelkader, A., Khan, M., Neishaboori, A., Harras, K. A. and Mohamed, A., “Argus: Realistic Target Coverage by Drones,” Proceedings of the 16th ACM/IEEE International Conference on Information Processing in Sensor Networks, Pittsburgh, PA, USA (2017) pp. 155–166. http://doi.acm.org/10.1145/3055031.3055078.Google Scholar
9. Aurenhammer, F., “Power diagrams: Properties, algorithms and applications,” SIAM J. Comput. 16 (1), 78–96 (1987). https://doi.org/10.1137/0216006.Google Scholar
10. Emiris, I. Z. and Karavelas, M. I., “The predicates of the apollonius diagram: Algorithmic analysis and implementation,” Comput. Geom. 33, 18–57 (2006). https://doi.org/10.1016/j.comgeo.2004.02.006.Google Scholar
11. Pimenta, L. C. A., Kumar, V., Mesquita, R. C. and Pereira, G. A. S., “Sensing and Coverage for a Network of Heterogeneous Robots,” Proceedings of the 47th IEEE Conference on Decision and Control, Cancun, Mexico (Dec. 2008) pp. 3947–3952. https://doi.org/10.1109/CDC.2008.4739194.Google Scholar
12. Bartolini, N., Calamoneri, T., La Porta, T. F. and Silvestri, S., “Autonomous deployment of heterogeneous mobile sensors,” IEEE Trans. Mobile Comput. 10 (6), 753–766 (2011). https://doi.org/10.1109/TMC.2010.192.Google Scholar
13. Thanou, M., Stergiopoulos, Y. and Tzes, A., “Distributed Coverage Mobile Heterogeneous Networks in Non-Convex Environments,” Proceedings of the 21st Mediterranean Conference on Control and Automation, Platanias-Chania, Crete, Greece (Jun. 2013) pp. 956–962. https://doi.org/10.1109/MED.2013.6608837.Google Scholar
14. Boardman, B., Harden, T. and Martínez, S., “Limited Range Spatial Load Balancing for Multiple Robots,” Proceedings of the American Control Conference, Seattle, WA, USA (May 2017) pp. 2285–2290. https://doi.org/10.23919/ACC.2017.7963293.Google Scholar
15. Stergiopoulos, Y. and Tzes, A., “Autonomous Deployment of Heterogeneous Mobile Agents with Arbitrarily Anisotropic Sensing Patterns,” Proceedings of the 20th Mediterranean Conference on Control and Automation, Barcellona, Spain (Jul. 2012) pp. 1585–1590. https://doi.org/10.1109/MED.2012.6265865.Google Scholar
16. Stergiopoulos, Y. and Tzes, A., “Cooperative Positioning-Orientation Control of Mobile Heterogeneous Anisotropic Sensor Networks for Area Coverage,” Proceedings of the IEEE International Conference on Robotics and Automation, Hong Kong, China (May 2014) pp. 1106–1111. https://doi.org/10.1109/ICRA.2014.6906992.Google Scholar
17. Gusrialdi, A., Hatanaka, T. and Fujita, M., “Coverage Control for Mobile Networks with Limited-Range Anisotropic Sensors,” Proceedings of the 47th IEEE Conference on Decision and Control, Cancun, Mexico (Dec. 2008) pp. 4263–4268. https://doi.org/10.1109/CDC.2008.4739007.Google Scholar
18. Laventall, K. and Cortés, J., “Coverage Control by Robotic Networks with Limited-Range Anisotropic Sensory,” Proceedings of the American Control Conference, Seattle, WA, USA (Jun. 2008) pp. 2666–2671. https://doi.org/10.1109/ACC.2008.4586895.Google Scholar
19. Hexsel, B., Chakraborty, N. and Sycara, K., “Coverage Control for Mobile Anisotropic Sensor Networks,” Proceedings of the IEEE International Conference on Robotics and Automation, Shanghai, China (May 2011) pp. 2878–2885. https://doi.org/10.1109/ICRA.2011.5980370.Google Scholar
20. Hexsel, B., Chakraborty, N. and Sycara, K., “Distributed coverage control for mobile anisotropic sensor networks,” Technical Report CMU-RI-TR-13-01, Robotics Institute, Pittsburgh, PA, USA (Jan. 2013).Google Scholar
21. Kantaros, Y., Thanou, M. and Tzes, A., “Visibility-Oriented Coverage Control of Mobile Robotic Networks on Non-Convex Regions,” Proceedings of the IEEE International Conference on Robotics and Automation, Hong Kong, China (Sep. 2014) pp. 1126–1131. https://doi.org/10.1109/ICRA.2014.6906995.Google Scholar
22. Avellar, G. S. C., Pereira, G. A. S., Pimenta, L. C. A. and Iscold, P., “Multi-UAV routing for area coverage and remote sensing with minimum time,” Sensors 15 (11), 27783–27803 (2015). http://dx.doi.org/10.3390/s151127783.Google Scholar
23. Acevedo, J. J., Arrue, B. C., Maza, I. and Ollero, A., “Distributed approach for coverage and patrolling missions with a team of heterogeneous aerial robots under communication constraints,” Int. J. Adv. Robot. Syst. 10 (1), (2013) pp. 28(1)–28(13). https://doi.org/10.5772/52765.Google Scholar
24. Acevedo, J. J., Arrue, B. C., Maza, I. and Ollero, A., “A Decentralized Algorithm for Area Surveillance Missions Using a Team of Aerial Robots with Different Sensing Capabilities,” Proceedings of the IEEE International Conference on Robotics and Automation, Hong Kong, China (May 2014) pp. 4735–4740. https://doi.org/10.1109/ICRA.2014.6907552.Google Scholar
25. Acevedo, J. J., Arrue, B. C., Maza, I. and Ollero, A., “A distributed algorithm for area partitioning in grid-shape and vector-shape configurations with multiple aerial robots,” J. Intell. Robot. Syst. 84 (1), 543–557 (2016). https://doi.org/10.1007/s10846-015-0272-5.Google Scholar
26. Enright, J., Savla, K. and Frazzoli, E., “Coverage Control of Nonholomonic Agents,” Proceedings of the 47th IEEE Conference on Decision and Control, Cancun, Mexico (Dec. 2008) pp. 4250–4256. https://doi.org/10.1109/CDC.2008.4739379.Google Scholar
27. Mathew, G. and Surana, A., “A Static Coverage Algorithm for Locational Optimization,” Proceedings of the 51st IEEE Conference on Decision and Control, Maui, HI, USA (Dec. 2012) pp. 806–811. https://doi.org/10.1109/CDC.2012.6426561.Google Scholar
28. Luna, J. M., Fierro, R., Abdallah, C. T. and Wood, J., “An adaptive coverage control for deployment of nonholonomic mobile sensor networks over time-varying sensory functions,” Asian J. Control 15 (4), 988–1000 (2013). http://dx.doi.org/10.1002/asjc.636.Google Scholar
29. Sharifi, F., Chamseddine, A., Mahboubi, H., Zhang, Y. and Aghdam, A. G., “A distributed deployment strategy for a network of cooperative autonomous vehicles,” IEEE Trans. Control Syst. Technol. 23 (2), 737–745 (2015). https://doi.org/10.1109/TCST.2014.2341658.Google Scholar
30. Fabiani, F., Fenucci, D., Fabbri, T. and Caiti, A, “A distributed, passivity-based control of autonomous mobile sensors in an underwater acoustic network,” IFAC-PapersOnLine 49 (23), 367–372 (2016). https://doi.org/10.1016/j.ifacol.2016.10.432.Google Scholar
31. Razak, R. A., Sukumar, S. and Chung, H., “Decentralized adaptive coverage control of nonholonomic mobile robots,” IFAC-PapersOnLine 49 (18), 410–415 (2016). https://doi.org/10.1016/j.ifacol.2016.10.200.Google Scholar
32. Kwok, A. and Martínez, S., “Deployment algorithms for a power-constrained mobile sensor network,” Int. J. Robust Nonlinear Control 20 (7), 745–763 (2010). http://dx.doi.org/10.1002/rnc.1464.Google Scholar
33. Ru, Y. and Martínez, S., “Coverage control in constant flow environments based on a mixed energy-time metric,” Automatica 49 (9), 2632–2640 (2013). https://doi.org/10.1016/j.automatica.2013.05.024.Google Scholar
34. Song, Y., Wang, B., Shi, Z., Pattipati, K. R. and Gupta, S., “Distributed algorithms for energy-efficient even self-deployment in mobile sensor networks,” IEEE Trans. Mobile Comput. 13 (5), 1035–1047 (2014). https://doi.org/10.1109/TMC.2013.46.Google Scholar
35. Moarref, M. and Rodrigues, L., “An optimal control approach to decentralized energy-efficient coverage problems,” IFAC Proc. Vol. 47 (3), 6038–6043 (2014). Proc. 19th IFAC World Congress, https://doi.org/10.3182/20140824-6-ZA-1003.01625.Google Scholar
36. Nguyen, M. T., Rodrigues, L., Maniu, C. S. and Olaru, S., “Discretized Optimal Control Approach for Dynamic Multi-Agent Decentralized Coverage,” Proceedings of the IEEE International Symposium on Intelligent Control, Buenos Aires, Argentina (Sep. 2016) pp. 335–340. https://doi.org/10.1109/ISIC.2016.7579984.Google Scholar
37. Nguyen, M. T., Stoica Maniu, C. and Olaru, S., “Optimization-based control for multi-agent deployment via dynamic Voronoi partition,” IFAC-PapersOnLine 50 (1), 1828–1833 (2017).https://doi.org/10.1016/j.ifacol.2017.08.185.Google Scholar
38. Niccolini, M., Innocenti, M. and Pollini, L., “Near Optimal Swarm Deployment Using Descriptor Functions,” Proceedings of the IEEE International Conference on Robotics and Automation, Anchorage, AK, USA (May 2010) pp. 4952–4957. https://doi.org/10.1109/ROBOT.2010.5509984.Google Scholar
39. Ferrari Braga, A., Innocenti, M. and Pollini, L., “Multi-Agent Coordination with Arbitrarily Shaped Descriptor Function,” Proceedings of the AIAA Guidance, Navigation and Control Conference, Boston, MA, USA (Aug. 2013). https://doi.org/10.2514/6.2013-4996.Google Scholar
40. Niccolini, M., Pollini, L. and Innocenti, M., “Cooperative control for multiple autonomous vehicles using descriptor functions,” J. Sensor Actuator Netw. 3 (1), 26–43 (2014). http://dx.doi.org/10.3390/jsan3010026.Google Scholar
41. Franzini, G., Aringhieri, S., Fabbri, T., Razzanelli, M., Pollini, L. and Innocenti, M., “Human-Machine Interface for Multi-Agent Systems Management using the Descriptor Function Framework,” In: Modelling and Simulation for Autonomous Systems, 3rd International Workshop, MESAS 2016, Rome, Italy, June 15–16. 2016, Revised Selected Papers (Hodicky, J., eds.) (Springer International Publishing, 2016) pp. 25–39. https://doi.org/10.1007/978-3-319-47605-6_3.Google Scholar
42. Niccolini, M., Swarm Abstractions for Distributed Estimation and Control Ph.D. Thesis (Pisa: University of of Pisa, Jul. 2011).Google Scholar
43. Engwerda, J., LQ Dynamic Optimization and Differential Games (John Wiley & Sons Ltd, Chichester, West Sussex, England, 2005).Google Scholar
44. Shoam, Y. and Leyton-Brown, K., Multiagent Systems – Algorithmic, Game-Theoretic, and Logical Foundations (Cambridge University Press, New York, USA, 2009).Google Scholar
45. Caiti, A., Fabbri, T., Fenucci, D. and Munafò, A., “Potential Games and AUVs Cooperation: First Results from the THESAURUS Project,” Proceedings of the MTS/IEEE OCEANS, Bergen, Norway (2013). https://doi.org/10.1109/OCEANS-Bergen.2013.6608165.Google Scholar
46. Marden, J. R., Arslan, G. and Shamma, J. S., “Cooperative control and potential games,” IEEE Trans. Syst., Man, Cybern. - Part B: Cybern. 39 (6), 1393–1407 (2009). https://doi.org/10.1109/TSMCB.2009.2017273.Google Scholar
47. Dürr, H.-B., Stanković, M. S. and Johansson, K. H., “Distributed Positioning of Autonomous Mobile Sensors with Application to Coverage Control,” Proceedings of the American Control Conference, San Francisco, CA, USA (Jun. 2008) pp. 4822–4827. https://doi.org/10.1109/ACC.2011.5991324.Google Scholar
48. Saridis, G. N. and Lee, C.-S. G., “An approximation theory of optimal control for trainable manipulators,” IEEE Trans. Syst. Man, Cybern. 9 (3), 152–159 (1979). https://doi.org/10.1109/TSMC.1979.4310171.Google Scholar
49. Isidori, A., Nonlinear Control Systems, 3rd ed. (Springer-Verlag, London, 1995).Google Scholar
50. Hussein, I. I. and Stipanović, D. M., “Effective coverage control for mobile sensor networks with guaranteed collision avoidance,” IEEE Trans. Control Syst. Technol. 15 (4), 642–657 (2007). https://doi.org/10.1109/TCST.2007.899155.Google Scholar
51. Stipanović, D. M., Hokayem, P. F., Spong, M. W. and Šiljak, D. D., “Cooperative avoidance control for multiagent systems,” J. Dyn. Syst. Meas. Control 129, 699–707 (2007). https://doi.org/10.1115/1.2764510.Google Scholar
52. Beard, R. W., Saridis, G. N. and Wen, J. T., “Galerkin approximations of the Generalized Hamilton–Jacobi–Bellman equation,” Automatica 33 (12), 2159–2177 (1997). https://doi.org/10.1016/S0005-1098(97)00128-3.Google Scholar
53. Beard, R. W., Saridis, G. N. and Wen, J. T., “Approximate solutions to the time-invariant Hamilton–Jacobi–Bellman equation,” J. Optim. Theory Appl. 96 (3), 589–626 (1998). https://doi.org/10.1023/A:1022664528457.Google Scholar
54. Park, C. and Tsiotras, P., “Approximations to Optimal Feedback Control Using a Successive Wavelet Collocation Algorithm,” Proceedings of the American Control Conference, Denver, CO, USA (Jun. 2003) pp. 1950–1955. https://doi.org/10.1109/ACC.2003.1243359.Google Scholar
55. Chen, Z. and Jagannathan, S., “Generalized Hamilton–Jacobi–Bellman formulation-based neural network control of affine nonlinear discrete-time systems,” IEEE Trans. Neural Netw. 19 (1), 90–106 (2008). https://doi.org/10.1109/TNN.2007.900227.Google Scholar
56. Athans, M. and Falb, P. L., Optimal Control: An Introduction to the Theory and Its Applications (McGraw-Hill, New York, USA, 1966).Google Scholar