Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-25T09:11:52.860Z Has data issue: false hasContentIssue false
  • English
  • Français

Communication-free autonomous cooperative circumnavigation of unpredictable dynamic objects

Published online by Cambridge University Press:  09 June 2021

A. S. Matveev Open the ORCID record for A. S. Matveev [Opens in a new window]  and
V. V. Magerkin
A. S. Matveev*
Affiliation:
Department of Mathematics and Mechanics, Saint Petersburg University, Universitetskii 28, Petrodvoretz, St.Petersburg 198504, Russia Faculty of Control Systems and Robotics, ITMO University, 49 Kronverksky Pr., St. Petersburg 197101, Russia
V. V. Magerkin
Affiliation:
Department of Mathematics and Mechanics, Saint Petersburg University, Universitetskii 28, Petrodvoretz, St.Petersburg 198504, Russia
*
*Corresponding author. Email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Each of several speed-limited planar robots is driven by the acceleration, limited in magnitude. There is an unpredictable dynamic complex object, for example, a group of moving targets or an extended moving and deforming body. The robots should reach and then repeatedly trace a certain object-dependent moving and deforming curve that encircles the object and also achieve an effective self-deployment over it. This may be, for example, the locus of points at a desired mean distance or distance from a group of targets or a single extended object, respectively. Every robot has access to the nearest point of the curve and its own velocity and “sees” the objects within a finite sensing range. The robots have no communication facilities, cannot differentiate the peers, and are to be driven by a common law. Necessary conditions for the solvability of the mission are established. Under their slight and partly unavoidable enhancement, a new decentralized control strategy is proposed and shown to solve the mission, while excluding inter-robot collisions, and for the case of a steady curve, to evenly distribute the robots over the curve and to ensure a prespecified speed of their motion over it. These are justified via rigorous global convergence results and confirmed via computer simulations.

Keywords

autonomous sensor-based reactive navigationmultirobot scenariounpredictably moving curvecurve trackingeffective self-deploymentglobal convergence
Type
Article
Information
Robotica , Volume 40 , Issue 3 , March 2022 , pp. 520 - 543
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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

Oh, K., Park, M. and Ahn, H., “A survey of multi-agent formation control,” Automatica 53, 424–440 (2015).CrossRefGoogle Scholar
Ren, W. and Cao, Y., Distributed Coordination of Multi-agent Networks: Emergent Problems, Models, and Issues (Springer-Verlag, London, 2010)Google Scholar
Ceccarelli, N., DiMarco, M., Garulli, A. and Giannitrapani, A., “Collective circular motion of multi-vehicle systems,” Automatica 44(12), 3025–3035 (2008).CrossRefGoogle Scholar
Guo, J., Yan, G. and Lin, Zh., “Local control strategy for moving-target-enclosing under dynamically changing network topology,” Syst. Control Lett. 59(10), 654–661 (2010).CrossRefGoogle Scholar
Kawakami, H. and Namerikawa, T., “Cooperative Target-Capturing Strategy for Multi-Vehicle Systems with Dynamic Network Topology,” Proceedings of the 2009 ACC (2009) pp. 635–640.Google Scholar
Kim, T., Harab, Sh. and Hori, Y., “Cooperative control of multi-agent dynamical systems in target-enclosing operations using cyclic pursuit strategy,” Int. J. Control 83(10), 2040–2052 (2010).Google Scholar
Kim, T. and Sugie, T., “Cooperative control for target-capturing task based on a cyclic pursuit strategy,” Automatica 43(8), 1426–1431 (2007).CrossRefGoogle Scholar
Kobayashi, Y. and Hosoe, Sh., “Cooperative enclosing and grasping of an object by decentralized mobile robots using local observation,” Int. J. Soc. Rob. 4(1), 19–32 (2012).CrossRefGoogle Scholar
Kothari, M., Sharma, R., Postlethwaite, I., Beard, R. and Pack, D., “Cooperative target-capturing with incomplete target information,” Int. J. Intell. Rob. Syst. 72(3–4), 373–384 (2013).CrossRefGoogle Scholar
Lan, Y., Yan, G., and Lin, Zh., “Distributed control of cooperative target enclosing based on reachability and invariance analysis,” Syst. Control Lett. 59(7), 381–389 (2010).CrossRefGoogle Scholar
Marshall, J. A., Broucke, M. E. and Francis, B. A., “Pursuit formations of unicycles,” Automatica 42(1), 3–12 (2006).CrossRefGoogle Scholar
Shames, I., Fidan, B. and Anderson, B. D. O., “Close target reconnaissance with guaranteed collision avoidance,” Int. J. Robust Nonlinear Control 21(16), 1823–1840 (2011).Google Scholar
Sinha, A. and Ghose, D., “Generalization of nonlinear cyclic pursuit,” Automatica 43(11), 1954–1960 (2007).Google Scholar
Tsumura, K., Hara, S., Sakurai, K. and Kim, T. H., “Performance competition in cooperative capturing by multi-agent systems,” SICE J. Control Meas. Syst. Integr. 4(3), 221–229 (2011).CrossRefGoogle Scholar
Yamaguchi, H., “A distributed motion coordination strategy for multiple nonholonomic mobile robots in cooperative hunting operations,” Rob. Auto. Syst. 43(4), 257–282 (2003).CrossRefGoogle Scholar
Zakhar’eva, A., Matveev, A. S., Hoy, M. C. and Savkin, A. V., “A strategy for target capturing with collision avoidance for non-holonomic robots with sector vision and range-only measurements,” Robotica 33(2), 385–412 (2015).CrossRefGoogle Scholar
Savkin, A. V., Cheng, T. M., Xi, Z., Javed, F., Matveev, A. S. and Nguyen, H., Decentralized Coverage Control Problems for Mobile Robotic Sensor and Actuator Networks (Wiley and IEEE Press, Hoboken, NJ, 2015)CrossRefGoogle Scholar
Sato, K. and Maeda, N., “Target-Enclosing Strategies for Multi-Agent Using Adaptive Control Strategy,” Proceedings of the 2010 IEEE International Conference on Control Applications (2010) pp. 1761–1766.Google Scholar
Matveev, A. S. and Ovchinnikov, K. S., “Circumnavigation of a speedy unpredictable target by a group of speed- and acceleration-limited robots,” Int. J. Robust Nonlinear Control 29(4), 1063–1087 (2019).CrossRefGoogle Scholar
Deghat, M., Xia, L., Anderson, B. D. O. and Hong, Y., “Multi-target localization and circumnavigation by a single agent using bearing measurements,” Int. J. Robust Nonlinear Control 25(14), 2362–2374 (2015).CrossRefGoogle Scholar
Matveev, A. S., Semakova, A. A. and Savkin, A. V., “Range-only based circumnavigation of a group of moving targets by a non-holonomic mobile robot,” Automatica 65, 76–89 (2016).CrossRefGoogle Scholar
Matveev, A. S., Semakova, A. A. and Savkin, A. V., “Tight circumnavigation of multiple moving targets based on a new method of tracking environmental boundaries,” Automatica 79, 52–60 (2017).CrossRefGoogle Scholar
Ovchinnikov, K. S., Semakova, A. A. and Matveev, A. S., “Cooperative surveillance of unknown environmental boundaries by multiple nonholonomic robots,” Rob. Auto. Syst. 72, 164–180 (2015).CrossRefGoogle Scholar
Matveev, A. S., Wang, C. and Savkin, A. V, “Real-time navigation of mobile robots in problems of border patrolling and avoiding collisions with moving and deforming obstacles,” Rob. Auto. Syst. 60(6), 769–788 (2012).CrossRefGoogle Scholar
Spencer, J. A. M., Continuum Mechanics (Dover Publications, NY, 2004)Google Scholar
Matveev, A. S., Teimoori, H. and Savkin, A. V., “A method for guidance and control of an autonomous vehicle in problems of border patrolling and obstacle avoidance,” Automatica 47(3), 515–524 (2011).CrossRefGoogle Scholar
Filippov, A. F., Differential Equations with Discontinuous Righthand Sides (Kluwer Academic Publishers, Dordrecht, the Netherlands, 1988).CrossRefGoogle Scholar
Altenbach, H. and Öchsner, A., (eds.), Encyclopedia of Continuum Mechanics (Springer, Berlin, 2020)Google Scholar
Matveev, A. S. and Magerkin, V. V., “Robotic following of flexible extended objects: Relevant technical facts on the kinematics of a moving continuum,” ArXiv 2012.13240 (2020).Google Scholar
Danskin, J. M., “The theory of min-max, with applications,” SIAM J. Appl. Math. 14(4), 641–644 (1966).CrossRefGoogle Scholar
Hartman, P., Ordinary Differential Equations, 2nd edn. (Birkhäuzer, Boston, 1982).Google Scholar