Design and Calibration of a Lightweight Physics-Based Model for Fluid-Mediated Self-assembly of Robotic Modules
In this paper, we consider a system consisting of multiple floating robotic modules performing self-assembly. Faithfully modeling such a system and its inter-module interactions typically involves capturing the hydrodynamic forces acting on the modules using computationally expensive fluid dynamic modeling tools. This poses restrictions on the usability of the resulting models. Here, we present a new approach towards modeling such systems. First, we show how the hardware and firmware of the robotic modules can be faithfully modeled in a high-fidelity robotic simulator. Second, we develop a physics plugin to recreate the hydrodynamic forces acting on the modules and propose a trajectory-based method for calibrating the plugin model parameters. Our calibration method employs a Particle Swarm Optimization (PSO) algorithm, and consists of minimizing the difference between Mean Squared Displacement (MSD) data extracted from real and simulated trajectories of multiple robotic modules.
This work has been partially sponsored by the Swiss National Science Foundation under the grant numbers 200021_137838/1 and 200020_157191/1.
- 1.Di Mario, E., Mermoud, G., Mastrangeli, M., Martinoli, A.: A trajectory-based calibration method for stochastic motion models. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 4341–4347 (2011)Google Scholar
- 4.Haghighat, B., Droz, E., Martinoli, A.: Lily: a miniature floating robotic platform for programmable stochastic self-assembly. In: IEEE International Conference on Robotics and Automation, pp. 1941–1948 (2015)Google Scholar
- 5.Haghighat, B., Martinoli, A.: Characterization and validation of a novel robotic system for fluid-mediated programmable stochastic self-assembly. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2778–2783 (2016)Google Scholar
- 7.Jacot-Descombes, L.: Fluid-mediated Self-assembly of MEMS Micro-capsules for Liquid Encapsulation and Release. Ph.D. thesis (2013)Google Scholar
- 8.Lochmatter, T., Roduit, P., Cianci, C., Correll, N., Jacot, J., Martinoli, A.: Swistrack-a flexible open source tracking software for multi-agent systems. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 4004–4010 (2008)Google Scholar
- 9.Matthey, L., Berman, S., Kumar, V.: Stochastic strategies for a swarm robotic assembly system. In: IEEE International Conference on Robotics and Automation, pp. 1953–1958 (2009)Google Scholar
- 10.Michel, O.: Webots: professional mobile robot simulation. Adv. Robot. Syst. 1(1), 39–42 (2004)Google Scholar
- 12.Pedersen, M.E.H.: Good parameters for particle swarm optimization. Hvass Lab., Copenhagen, Denmark, Technical Report. HL1001 (2010)Google Scholar