Hostname: page-component-8448b6f56d-c47g7 Total loading time: 0 Render date: 2024-04-24T19:09:13.060Z Has data issue: false hasContentIssue false
  • English
  • Français

Robust and reversible execution of self-reconfiguration sequences†

Published online by Cambridge University Press:  14 January 2011

Ulrik Schultz ,
Mirko Bordignon  and
Kasper Stoy
Ulrik Schultz*
Affiliation:
Modular Robotics Lab, Maersk Mc-Kinney Moller Institute, Faculty of Engineering, University of Southern Denmark, Denmark
Mirko Bordignon
Affiliation:
Modular Robotics Lab, Maersk Mc-Kinney Moller Institute, Faculty of Engineering, University of Southern Denmark, Denmark
Kasper Stoy
Affiliation:
Modular Robotics Lab, Maersk Mc-Kinney Moller Institute, Faculty of Engineering, University of Southern Denmark, Denmark
*
*Corresponding author. E-mail: ups@mmmi.sdu.dk
Get access Rights & Permissions [Opens in a new window]

Summary

Modular, self-reconfigurable robots are robotic systems that can change their own shape by autonomously rearranging the physical modules from which they are built. In this work, we are interested in how to distributedly execute a specified self-reconfiguration sequence. The sequence is specified using a simple and centralized scripting language, which either could be the outcome of a planner or be hand-coded. The distributed controller generated from this language allows for parallel self-reconfiguration steps and is highly robust to communication errors and loss of local state due to software failures. Furthermore, the self-reconfiguration sequence can automatically be reversed, if desired. We verify our approach and demonstrate its robustness in experiments using physical and the simulated ATRON modules, as well as simulated M-TRAN modules. Overall, the contribution of this work is the combination of the tractability of a centralized scripting language with the robustness and parallelism of distributed controllers in modular robots.

Keywords

Modular RobotsControl of Robotic SystemsRobotic Self-Diagnosis and Self-RepairRobotic Self-ReplicationSensor Networks
Type
Article
Information
Robotica , Volume 29 , Special Issue 1: Robotic Self-X Systems , January 2011 , pp. 35 - 57
Copyright
Copyright © Cambridge University Press 2011

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.)

Footnotes

†

This work was supported by the Danish Council for Independent Research.

References

1.Asadpour, M., Ashtiani, M. H. Z., Sproewitz, A. and Ijspeert, A., “Graph Signature for Self-Reconfiguration Planning of Modules with Symmetry,” Proceedings of the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), St. Louis, USA (2009).Google Scholar
2.Asadpour, M., Sproewitz, A., Billard, A., Dillenbourg, P. and Ijspeert, A., “Graph Signature for Self-Reconfiguration Planning,” Proceedings of the 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'08), Nice, France (2008) pp. 863–869.Google Scholar
3.Ashley-Rollman, M. P., Goldstein, S. C., Lee, P., Mowry, T. C. and Pillai, P., “Meld: A Declarative Approach to Programming Ensembles,” Proceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'07), San Diego, CA, USA (2007) pp. 2794–2800.Google Scholar
4.Baillie, J.-C., Demaille, A., Hocquet, Q., Nottale, M. and Tardieu, S., “The Urbi Universal Platform for Robotics,” Proceedings of the SIMPAR'08 Workshop on Standards and Common Platform for Robotics, Venice, Italy (2008).Google Scholar
5.Bordignon, M., Christensen, D. J., Stoy, K. and Schultz, U. P., “Elements of a Development Ecosystem for Modular Robot Applications,” Proceedings of the Fourth International Workshop on Software Development and Integration in Robotics (SDIR'09), Kobe, Japan (2009a).Google Scholar
6.Bordignon, M., Lindegaard Mikkelsen, L. and Schultz, U. P., “Implementing Flexible Parallelism for Modular Self-Reconfigurable Robots,” Proceedings of the International Conference on Simulation, Modeling and Programming for Autonomous Robots (SIMPAR'08), Venice, Italy (2008) pp. 123–134.CrossRefGoogle Scholar
7.Bordignon, M., Stoy, K. and Schultz, U. P., “A Virtual Machine-Based Approach for Fast and Flexible Reprogramming of Modular Robots,” Proceedings of the IEEE International Conference on Robotics and Automation (ICRA'09), Kobe, Japan (2009b) pp. 4273–4280.Google Scholar
8.Brandt, D., “Comparison of A* and RRT-connect Motion Planning Techniques for Self-Reconfiguration Planning,” Proceedings of the 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'06), Beijing, China (2006) pp. 892–897.Google Scholar
9.Brandt, D., “Scalability and Complexity of Self-Reconfigurable Robot Control PhD Thesis (University of Southern Denmark: The Maersk Institute, 2007).Google Scholar
10.Brandt, D. and Christensen, D. J., “A New Meta-Module for Controlling Large Sheets of ATRON Modules,” Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, San Diego, CA (2007) pp. 2375–2380.Google Scholar
11.Brandt, D., Larsen, J. C., Christensen, D. J., Garcia, R. F. Mendoza, Shaikh, D., Schultz, U. P. and Stoy, K., “Flexible, FPGA-Based Electronics for Modular Robots,” Proceedings of the IROS'08 Workshop on Self-Reconfigurable Robots & Systems and Applications, Nice, France (2008).Google Scholar
12.Butler, Z. and Rus, D., “Distributed planning and control for modular robots with unit-compressible modules,” Int. J. Robot. Res. 22 (9), 699–715 (2003).CrossRefGoogle Scholar
13.Christensen, D. J., Bordignon, M., Schultz, U. P., Shaikh, D. and Stoy, K., “Morphology Independent Learning in Modular Robots,” Proceedings of the International Symposium on Distributed Autonomous Robotic Systems (DARS'08), Tsukuba, Japan (2008a) pp. 379–391.Google Scholar
14.Christensen, D. J., Brandt, D., Stoy, K. and Schultz, U. P., “A Unified Simulator for Self-Reconfigurable Robots,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'08), France (2008b) pp. 870–876.Google Scholar
15.Christensen, D. J. and Stoy, K., “Selecting a Meta-Module to Shape-Change the ATRON Self-Reconfigurable Robot,” Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Orlando, FL (2006) pp. 2532–2538.Google Scholar
16.Cohen, P., Empirical Methods for Artificial Intelligence (MIT Press, Cambridge, MA, 1995).Google Scholar
17.De Rosa, M., Goldstein, S. C., Lee, P., Campbell, J. D. and Pillai, P., “Programming Modular Robots with Locally Distributed Predicates,” Proceedings of the 2008 IEEE International Conference on Robotics and Automation (ICRA'08), Pasadena, CA, USA (2008) pp. 3156–3162.CrossRefGoogle Scholar
18.Goldstein, S. C., Campbell, J. D. and Mowry, T. C., “Programmable matter,” IEEE Comput. 38 (6), 99–101 (2005).CrossRefGoogle Scholar
19.Intanagonwiwat, C., Govindan, R. and Estrin, D., “Directed Diffusion: A Scalable and Robust Communication Paradigm for Sensor Networks,” MobiCom '00: Proceedings of the 6th Annual International Conference on Mobile Computing and Networking, New York, NY, USA, ACM Press (2000) pp. 56–67.CrossRefGoogle Scholar
20.Klues, K., Handziski, V., Culler, D., Gay, D., Levis, P., Lu, C. and Wolisz, A., “Dynamic Resource Management in a Static Network Operating System,” Tech. Rep. WUCSE-2006-56 (Washington University in St. Louis, 2006).Google Scholar
21.Kokaji, S., Murata, S., Kurokawa, H. and Tomita, K., “Clock synchronization algorithm for a distributed autonomous system,” J. Robot. Mechatronics 8 (5), 317–338 (1996).Google Scholar
22.Kotay, K. and Rus, D., “Algorithms for Self-Reconfiguring Molecule Motion Planning,” Proceedings of the International Conference on Intelligent Robots and Systems (IROS'00), Takamatsu, Japan (2000) pp. 2184–2193.Google Scholar
23.Murata, S., Kurokawa, H. and Kokaji, S., “Self-assembling machine,” Proceedings of IEEE International Conference on Robotics and Automation (ICRA'94) (1994) pp. 441–448.Google Scholar
24.Østergaard, E., Kassow, K., Beck, R. and Lund, H., “Design of the ATRON lattice-based self-reconfigurable robot,” Auton. Robots 21 (2), 165–183 (2006).CrossRefGoogle Scholar
25.Pamecha, A., Ebert-Uphoff, I. and Chirikjian, G. S., “Useful metrics for modular robot motion planning,” IEEE Trans. Robot. Autom. 13, 531–545 (1997).CrossRefGoogle Scholar
26.Prevas, K., Unsal, C., Efe, M. and Khosla, P., “A Hierarchical Motion Planning Strategy for a Uniform Self-Reconfigurable Modular Robotic System,” Proceedings of the IEEE International Conference on Robotics and Automation (ICRA'02), Vol. 1, Washington DC (2002) pp. 787–792.Google Scholar
27.Rosa, M. D., Goldstein, S., Lee, P., Campbell, J. and Pillai, P., “Scalable Shape Sculpting via Hole Motion: Motion Planning in Lattice-Constrained Modular Robots,” Proceedings of the 2006 IEEE International Conference on Robotics and Automation (ICRA'06) (2006).Google Scholar
28.Shen, W.-M., Salemi, B. and Will, P., “Hormone-inspired adaptive communication and distributed control for CONRO self-reconfigurable robots,” IEEE Trans. Robot. Autom. 18, 700–712 (2002).CrossRefGoogle Scholar
29.Stoy, K., Christensen, D. J., Brandt, D., Bordignon, M. and Schultz, U. P., “Exploit Morphology to Simplify Docking of Self-Reconfigurable Robots,” Proceedings of the International Symposium on Distributed Autonomous Robotic Systems (DARS'08), Tsukuba, Japan (2008) pp. 441–452.Google Scholar
30.Ünsal, C. and Khosla, P., “A Multi-Layered Planner for Self-Reconfiguration of a Uniform Group of I-cube Modules,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'02), Vol. 1, Maoui, Hawaii (2002) pp. 598–605.Google Scholar
31.Ünsal, C., Kiliccöte, H. and Khosla, P. K., “A modular self-reconfigurable bipartite robotic system: Implementation and motion planning,” Auton. Robots 10, 23–40 (2001).CrossRefGoogle Scholar
32.Yim, M., Goldberg, D. and Casal, A., “Connectivity Planning for Closed-Chain Reconfiguration,” Proceedings of Sensor Fusion and Decentralized Control in Robotics Systems III, Vol. 4196, Bellingham, WA, SPIE (2000) pp. 402–412.CrossRefGoogle Scholar
33.Yim, M., Shen, W.-M., Salemi, B., Rus, D., Moll, M., Lipson, H., Klavins, E., and Chirikjian, G. S., “Modular self-reconfigurable robot systems [Grand Challenges of Robotics],” IEEE Robot. Autom. Mag. 14 (1), 43–52 (2007).CrossRefGoogle Scholar
34.Yim, M., Zhang, Y., Lamping, J. and Mao, E., “Distributed control for 3D metamorphosis,” Auton. Robots 10 (1), 41–56 (2001).CrossRefGoogle Scholar
35.Yokoyama, T., Axelsen, H. B. and Glück, R., “Principles of a reversible programming language,” CF '08: Proceedings of the 2008 Conference on Computing Frontiers (ACM, New York, NY, 2008) pp. 43–54.CrossRefGoogle Scholar
36.Yoshida, E., Murata, S., Kamimura, A., Tomita, K., Kurokawa, H. and Kokaji, S., “Motion Planning of Self-Reconfigurable Modular Robot,” Proceedings of the International Symposium on Experimental Robotics, Honolulu, Hawaii (2000) pp. 375–384.Google Scholar
37.Yoshida, E., Murata, S., Kurokawa, H., Tomita, K. and Kokaji, S., “A distributed method for reconfiguration of a three-dimensional homogeneous structure,” Adv. Robot. 13, 363–379 (1999a).CrossRefGoogle Scholar
38.Yoshida, E., Murata, S., Tomita, K., Kurokawa, H. and Kokaji, S., “An experimental study on a self-repairing modular machine,” Robot. Auton. Syst. 29, 79–89 (1999b).CrossRefGoogle Scholar
39.Zhang, Y., Golovinsky, A., Yim, M. and Eldershaw, C., “An XML-based Scripting Language for Chain-type Modular Robotic Systems,” Proceedings of the Conference on Intelligent Automous Systems (IAS-8), Amsterdam, Netherlands (2004) pp. 729–738.Google Scholar