ROBOTS MORPHOLOGIES AND COMMUNICATION STRATEGIES TRADE-OFF IN A DYNAMIC MULTI-ROBOT COLLABORATIVE ENVIRONMENT
Keywords:
Dynamic multi-robot system, Communication strategy, Robot morphology, Interaction, Collaborative environmentAbstract
Many robotic use cases stand in need of robot collaboration. Thus, it is vital to make sure that they collaborate effectively. While various dimensions of robots such as communication skills and morphology were studied independently, to our best knowledge, no anterior research has checked out those dimensions jointly. The aim of this article is to demonstrate the existence of an intrinsic relationship between morphology and communication strategies. In our study, we present collaborative scenario simulation results demonstrating that both morphologies and communication strategies interact in complex ways. The bulk of these results are derived from multiple simulation runs with randomly generated initial conditions. We compared task execution times for different morphologies, using either implicit or explicit communication. Simulation results proved that implicit communication was the most suitable strategy for anthropomorphic robots, whereas explicit communication was the most appropriate for zoomorphic and functional robots. We plan to pursue this research by verifying our approach on real robot platforms, including a larger number of robots, and tackling new types of interaction.
References
(1) B.F. Florea, O. Grigore, M. Datcu, Multi-agent exploration based on constraints imposed with graph search algorithms, Rev. Roum. Sci. Techn. – Électrotechn. et Énerg., 62, 1, pp. 87–92 (2017).
(2) M. Zohaib, J. Iqbal, S.M. Pasha, A novel goal-oriented strategy for mobile robot navigation without sub-goals constraint, Rev. Roum. Sci. Techn. – Électrotechn. et Énerg., 63, 1, pp. 106–111 (2018).
(3) C. Paul, M. Lungarella, F. Lidia, Morphology, control, and passive dynamics, Robotics and Autonomous Systems, 54, pp. 617–618 (2006).
(4) A.I. Gal, L. Vladareanu, R.I. Munteanu, Sliding motion control with bond graph modeling applied on a robot leg, Rev. Roum. Sci. Techn. – Électrotechn. et Énerg., 60, 2, pp. 215–224 (2015).
(5) R.H. Elhachemi Amar, L. Benchikh, H. Dermeche, O. Bachir, Z. Ahmed-Faitih, Efficient trajectory reconstruction for robot programming by demonstration, Rev. Roum. Sci. Techn. – Électrotechn. et Énerg., 65, 1–2, pp. 117–121 (2020).
(6) B.S. Wood, Children and Communication: Verbal and Nonverbal Language Development, Prentice-Hall, Inc., Englewood Cliffs – New Jersey (1981).
(7) “Language”, https://www.merriam-webster.com/dictionary/language, Nov. 17. 2020.
(8) H.A. Yanco, J.L. Drury: Classifying human-robot interaction: An updated taxonomy, Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, pp. 2841-2846, Los Alamitos, CA, 2004.
(9) T. Fong, I. Nourbakhsh, K. Dautenhahn, A survey of socially interactive robots: Concepts, design, and applications, Technical Report CMU-RI-TR-02-29, Robotics Institute, Carnegie Mellon University, Pittsburg, p. 1–56, 2002.
(10) L.J. Wood, A. Zaraki, B. Robins, K. Dautenhahn, Developing Kaspar: a humanoid robot for children with autism, International Journal of Social Robotics, pp. 1–18 (2019).
(11) K. Akachi, K. Kaneko, N. Kanehira, S. Ota, G. Miyamori, M. Hirata, S. Kajita, F. Kanehiro: Development of humanoid robot HRP-3P, 5th IEEE-RAS International Conference on Humanoid Robots, pp. 50–55, Tsukuba, Japan (2005).
(12) D. Gouaillier, V. Hugel, P. Blazevic, C. Kilner, J. Monceaux, P. Lafourcade, B. Marnier, J. Serre, B. Maisonnier: The NAO humanoid: a combination of performance and affordability, ArXiv e-prints (2008).
(13) S. Shigemi, ASIMO and humanoid robot research at Honda. Humanoid Robotics: A Reference, Springer, Dordrecht, 2019.
(14) J. Retto, Sophia, first citizen robot of the world, ResearchGate https://www.researchgate.net, pp. 2–9 (2017).
(15) T.B. Lauwers, G.A. Kantor, R.L. Hollis: A dynamically stable single-wheeled mobile robot with inverse mouse-ball drive, Proceedings of the IEEE IEEE International Conference on Robotics and Automation, pp. 2884–2889, Orlando, FL, 2006.
(16) D. Ding, R.A. Cooper, S. Terashima, Y. Yang, R. Cooper, A study on the balance function of the IBOT™ transporter, RESNA 27th International Annual Conference, Orlando (2004).
(17) C. Breazeal, Towards sociable robots, Robots, and Autonomous Systems, 42, pp. 167–175 (2003).
(18) J. Pineau, M. Montemerlo, M. Pollack, N. Roy, S. Thrun, Towards robotic assistants in nursing homes: Challenges and Results, Robots and Autonomous Systems, 42, pp. 271–281 (2003).
(19) M. Scheeff, J. Pinto, K. Rahardja, S. Snibbe, R. Tow: Experiences with Sparky, a social robot, Socially Intelligent Agents, Multiagent Systems, Artificial Societies, and Simulated Organizations Series, pp. 173–180, Springer US (2002).
(20) L. Vladareanu, A. Curaj, R. I. Munteanu, Complex walking robot kinematics analysis and PLC multi-tasking control, Rev. Roum. Sci. Techn. – Électrotechn. et Énerg., 57, 1, pp. 90–99 (2012).
(21) Innovation and technology – Festo Corporate, https://www.festo.com/group/en/cms/9999.htm, Dec. 9. 2020.
(22) J.J. Faria, J.R.G. Dyer, R.O. Clément, I.D. Couzin, N. Holt, A.J.W. Ward, D. Waters, J. Krause, A novel method for investigating the collective behavior of fish: introducing ‘Robofish’, Behavioral Ecology and Sociobiology, 64, 8, pp. 1211–1218 (2010).
(23) A. Ramezani, J.W. Hurst, J.W. Grizzle, Performance analysis and feedback control of ATRIAS, A Three-dimensional bipedal robot, J. of Dynamic Systems, Measurement, and Control, 136, 2, pp. 021012–021012-12 (2013).
(24) G. Caprari, T. Estier, R. Siegwart, Fascination of downscaling–Alice the sugar cube robot, J. of Micro-Mechatronics, 1, pp. 177–189 (2002).
(25) F. Mondada, M. Bonani, X. Raemy, J. Pugh, C. Cianci, A. Klaptocz, S. Magnenat, J.-C. Zufferey, D. Floreano, A. Martinoli, The e-puck, a Robot Designed for Education in Engineering, Proceedings of the 9th Conference on Autonomous Robot Systems and Competitions, pp. 59-65, Castelo Branco, Portugal (2009).
(26) T. Krajník, V. Vonásek, D. Fiser, J. Faigl, AR-drone as a platform for robotic research and education, Research and Education in Robotics, Communications in Computer and Information Science, pp. 172-186, Springer Berlin Heidelberg (2011).
(27) E. Rohmer, S.P.N. Singh, M. Freese: V-REP: A versatile and scalable robot simulation framework, IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1321-1326, Tokyo, Japan (2013).
(28) K. Hirai, M. Hirose, Y. Haikawa, T. Takenaka, The development of Honda humanoid robot, Proc. of the IEEE International Conference on Robotics and Automation, pp. 1321-1326, Leuven, Belgium (1998).
(29) NAO the humanoid and programmable robot – SoftBank Robotics, https://www.softbankrobotics.com/emea/en/nao, Oct. 24. 2020.
(30) ACM-R5H - Robotic Infrastructure & Services Provider - Robot Center, https://www.robotcenter.co.uk/products/acm-r5h, Aug. 18. 2020.
(31) KUKA Industrial Robots – KUKA youBot, http://www.kukarobotics.com/en/products/education/youbot/, May. 05, 2019.
