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Autonomous Robots
Published in: Autonomous Robots 4/2018

17-11-2017

Timed abstractions for distributed cooperative manipulation

Authors: Christos K. Verginis, Dimos V. Dimarogonas

Published in: Autonomous Robots | Issue 4/2018

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Abstract

This paper addresses the problem of deriving well-defined timed abstractions for the decentralized cooperative manipulation of a single object by N robotic agents. In particular, we propose a distributed model-free control protocol for the trajectory tracking of the cooperatively manipulated object without necessitating feedback of the contact forces/torques or inter-agent communication. Certain prespecified performance functions determine the transient and steady state of the coupled object-agents system. The latter, along with a region partition of the workspace that depends on the physical volume of the object and the agents, allows us to define timed transitions for the coupled system among the derived workspace regions. Therefore, we abstract its motion as a finite transition system and, by employing standard automata-based methodologies, we define high level complex tasks for the object that can be encoded by timed temporal logics. In addition, we use load sharing coefficients to represent potential differences in power capabilities among the agents. Finally, realistic simulation studies verify the validity of the proposed scheme.
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Appendix
Available only for authorised users
Footnotes
1
We focus on robotic structures where such a function exists, which constitute the majority of cases.
 
2
It can be proven that if such a run exists, then there also exists a run that can be always represented as a finite prefix followed by infinite repetitions of a finite suffix (Baier et al. 2008).
 
3
Note that the nature of the quadrotors makes the whole system underactuated and values \(\phi _{r_j,r_{j'}}(t),\theta _{r_j,r_{j'}}(t) \ne 0\) are not possible to be achieved without interfering with \(p_{\scriptscriptstyle O}(t)\).
 
Literature
Adzkiya, D., De Schutter, B., & Abate, A. (2013). Finite abstractions of max-plus-linear systems. IEEE Transactions on Automatic Control, 58(12), 3039–3053.MathSciNetCrossRefMATH
Aksaray, D., Vasile, C.-I., & Belta, C. (2016). Dynamic routing of energy-aware vehicles with temporal logic constraints. Proceedings of the IEEE international conference on robotics and automation (ICRA) (pp. 3141–3146).
Baier, C., Katoen, J.-P., et al. (2008). Principles of model checking. Cambridge: MIT Press.MATH
Bechlioulis, C. P., & Rovithakis, G. A. (2014). A low-complexity global approximation-free control scheme with prescribed performance for unknown pure feedback systems. Automatica, 50(4), 1217–1226.MathSciNetCrossRefMATH
Belta, C., & Habets, L. C. (2006). Controlling a class of nonlinear systems on rectangles. IEEE Transactions on Automatic Control, 51(11), 1749–1759.MathSciNetCrossRefMATH
Belta, C., & Kumar, V. (2004). Abstraction and control for groups of robots. IEEE Transactions on robotics, 20(5), 865–875.CrossRef
Boskos, D., & Dimarogonas, D. V. (2015). Decentralized abstractions for feedback interconnected multi-agent systems. In Proceedings of the IEEE conference on decision and control (CDC) (pp. 282–287).
Caccavale, F., Chiacchio, P., Marino, A., & Villani, L. (2008). Six-dof impedance control of dual-arm cooperative manipulators. IEEE/ASME Transactions on Mechatronics, 13(5), 576–586.CrossRef
Chaimowicz, L., Campos, M. F. M., & Kumar, V. (2003). Hybrid systems modeling of cooperative robots. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 3, 4086–4091.
Chen, Y., Ding, X. C., Stefanescu, A., & Belta, C. (2012). Formal approach to the deployment of distributed robotic teams. IEEE Transactions on Robotics, 28(1), 158–171.CrossRef
Cheng, P., Fink, J., & Kumar, V. (2009). Abstractions and algorithms for cooperative multiple robot planar manipulation. In Robotics: Science and Systems IV, p. 143.
Diaz-Mercado, Y., Jones, A., Belta, C., & Egerstedt, M. (2015). Correct-by-construction control synthesis for multi-robot mixing. In Proceedings of the IEEE conference on decision and control (CDC) (pp. 221–226).
Erhart, S., & Hirche, S. (2013). Adaptive force/velocity control for multi-robot cooperative manipulation under uncertain kinematic parameters. In Proceedings of the IEEE/RSJ international conference on intelligent robots and systems (IROS) (pp. 307–314).
Filippidis, I., & Murray, R. M. (2016). Symbolic construction of gr (1) contracts for systems with full information. In Proceedings of the American control conference (ACC) (pp. 782–789).
Franchi, A., Petitti, A., & Rizzo, A. (2014). Distributed estimation of the inertial parameters of an unknown load via multi-robot manipulation. In IEEE conference on decision and control (CDC) (pp. 6111–6116).
Franchi, A., Petitti, A., & Rizzo, A. (2015). Decentralized parameter estimation and observation for cooperative mobile manipulation of an unknown load using noisy measurements. In IEEE international conference on robotics and automation (ICRA) (pp. 5517–5522).
Guo, M., Tumova, J., & Dimarogonas, D. V. (2014). Cooperative decentralized multi-agent control under local ltl tasks and connectivity constraints. In Proceedings of the IEEE international conference on decision and control (pp. 75–80).
He, K., Lahijanian, M., Kavraki, L. E., and Vardi, M. Y. (2015). Towards manipulation planning with temporal logic specifications. In Proceedings of the IEEE international conference on robotics and automation (ICRA) (pp. 346–352).
Heck, D., Kostic, D., Denasi, A., & Nijmeijer, H. (2013). Internal and external force-based impedance control for cooperative manipulation. In Proceedings of the IEEE European control conference (ECC) (pp. 2299–2304).
Karaman, S., & Frazzoli, E. (2011). Linear temporal logic vehicle routing with applications to multi-uav mission planning. International Journal of Robust and Nonlinear Control, 21(12), 1372–1395.MathSciNetCrossRefMATH
Kloetzer, M., & Belta, C. (2008). A fully automated framework for control of linear systems from temporal logic specifications. IEEE Transactions on Automatic Control, 53(1), 287–297.MathSciNetCrossRefMATH
Lionis, G., & Kyriakopoulos, K. J. (2005). Centralized motion planning for a group of micro agents manipulating a rigid object. In Proceedings of the IEEE international symposium on intelligent control, Mediterrean conference on control and automation (pp. 662–667).
Lippiello, V., & Ruggiero, F. (2012). Cartesian impedance control of a uav with a robotic arm. IFAC Proceedings Volumes, 45(22), 704–709.CrossRef
Liu, Y.-H., & Arimoto, S. (1998). Decentralized adaptive and nonadaptive position/force controllers for redundant manipulators in cooperations. The International Journal of Robotics Research, 17(3), 232–247.CrossRef
Markdahl, J., Karayiannidis, Y., & Hu, X. (2012). Cooperative object path following control by means of mobile manipulators: a switched systems approach. IFAC Proceedings Volumes, 45(22), 773–778.CrossRef
Michael, N., Fink, J., & Kumar, V. (2011). Cooperative manipulation and transportation with aerial robots. Autonomous Robots, 30(1), 73–86.CrossRefMATH
Muthusamy, R., & Kyrki, V. (2014). Decentralized approaches for cooperative grasp planning. In Proceedings of the international conference on control automation robotics & vision (ICARCV) (pp. 693–698).
Nikou, A., Tumova, J., & Dimarogonas, D. V. (2016). Cooperative task planning of multi-agent systems under timed temporal specifications. In Proceedings of the IEEE American control conference (ACC) (pp. 7104–7109).
Ouaknine, J., & Worrell, J. (2005). On the decidability of metric temporal logic. Annual IEEE symposium on logic in computer science (LICS’05) (pp. 188–197).
Palunko, I., Donner, P., Buss, M., & Hirche, S. (2014). Cooperative suspended object manipulation using reinforcement learning and energy-based control. In IEEE/RSJ international conference on intelligent robots and systems (IROS 2014) (pp. 885–891).
Parra-Vega, V., Sanchez, A., Izaguirre, C., Garcia, O., & Ruiz-Sanchez, F. (2013). Toward aerial grasping and manipulation with multiple uavs. Journal of Intelligent & Robotic Systems, 70(1–4), 575–593.CrossRef
Petitti, A., Franchi, A., Di Paola, D., & Rizzo, A. (2016). Decentralized motion control for cooperative manipulation with a team of networked mobile manipulators. In Proceedings of the IEEE international conference on robotics and automation (ICRA) (pp. 441–446).
Rohmer, E., Singh, S. P., & Freese, M. (2013). V-rep: a versatile and scalable robot simulation framework. In Proceedings of the international conference on intelligent robots and systems (IROS).
Rungger, M., Weber, A., & Reissig, G. (2015). State space grids for low complexity abstractions. In Proceedings of the IEEE conference on decision and control (CDC) (pp. 6139–6146).
Sontag, E. D. (2013). Mathematical control theory: Deterministic finite dimensional systems (Vol. 6). New York: Springer.
Souza, D., & Prabhakar, P. (2007). On the expressiveness of mtl in the pointwise and continuous semantics. International Journal on Software Tools for Technology Transfer, 9(1), 1–4.CrossRef
Stroupe, A., Huntsberger, T., Okon, A., & Aghazarian, H. (2005). Precision manipulation with cooperative robots. Multi-Robot Systems. From Swarms to Intelligent Automata, III, 235–248.
Sugar, T. G., & Kumar, V. (2002). Control of cooperating mobile manipulators. IEEE Transactions on robotics and automation, 18(1), 94–103.CrossRef
Szewczyk, J., Plumet, F., & Bidaud, P. (2002). Planning and controlling cooperating robots through distributed impedance. Journal of Robotic Systems, 19(6), 283–297.CrossRefMATH
Tanner, H. G., Loizou, S. G., & Kyriakopoulos, K. J. (2003). Nonholonomic navigation and control of cooperating mobile manipulators. IEEE Transactions on Robotics and Automation, 19(1), 53–64.
Tiwari, A. (2008). Abstractions for hybrid systems. Formal Methods in System Design, 32(1), 57–83.CrossRefMATH
Tsiamis, A., Tumova, J., Bechlioulis, C. P., Karras, G. C., Dimarogonas, D. V., & Kyriakopoulos, K. J. (2015a). Decentralized leader-follower control under high level goals without explicit communication. In Proceedings of the IEEE/RSJ international conference on intelligent robots and systems (IROS) (pp. 5790–5795).
Tsiamis, A., Verginis, C. K., Bechlioulis, C. P., & Kyriakopoulos, K. J. (2015b). Cooperative manipulation exploiting only implicit communication. In Proceedings of the IEEE/RSJ international conference on intelligent robots and systems (IROS) (pp. 864–869).
Verginis, C. K., & Dimarogonas, D. V. (2016). Distributed cooperative manipulation under timed temporal specifications. American Control Conference (ACC).
Wang, Z., & Schwager, M. (2016). Multi-robot manipulation without communication. Distributed Autonomous Robotic Systems, 112, 135–149.CrossRef
Yamashita, A., Arai, T., Ota, J., & Asama, H. (2003). Motion planning of multiple mobile robots for cooperative manipulation and transportation. IEEE Transactions on Robotics and Automation, 19(2), 223–237.CrossRef
Zamani, M., Mazo, M., & Abate, A. (2014). Finite abstractions of networked control systems. In Proceedings of the IEEE conference on decision and control (pp. 95–100).
Zhang, Z., & Cowlagi, R. V. (2016). Motion-planning with global temporal logic specifications for multiple nonholonomic robotic vehicles. In Proceedings of the American control conference (ACC) (pp. 7098–7103).
Metadata
Title
Timed abstractions for distributed cooperative manipulation
Authors
Christos K. Verginis
Dimos V. Dimarogonas
Publication date
17-11-2017
Publisher
Springer US
Published in
Autonomous Robots / Issue 4/2018
Print ISSN: 0929-5593
Electronic ISSN: 1573-7527
DOI
https://doi.org/10.1007/s10514-017-9672-7

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