Top-Down vs. Bottom-Up Model-Based Methodologies for Distributed Control: A Comparative Experimental Study
Model-based synthesis of distributed controllers for multi-robot systems is commonly approached in either a top-down or bottom-up fashion. In this paper, we investigate the experimental challenges of both approaches, with a special emphasis on resource-constrained miniature robots. We make our comparison through a case study in which a group of 2-cm-sized mobile robots screen the environment for undesirable features, and destroy or neutralize them. First, we solve this problem using a top-down approach that relies on a graph-based representation of the system, allowing for direct optimization using numerical techniques (e.g., linear and non-linear convex optimization) under very unrealistic assumptions (e.g., infinite number of robots, perfect localization, global communication, etc.). We show how one can relax these assumptions in the context of resource-constrained robots, and explain the resulting impact on system performance. Second, we solve the same problem using a bottom-up approach, i.e., we build up computationally efficient and accurate models at multiple abstraction levels, and use them to optimize the robots’ controller using evolutionary algorithms. Finally, we outline the differences between the top-down and bottom-up approaches, and experimentally compare their performance.
KeywordsMobile Robot Multiagent System Chemical Reaction Network Finite State Machine Central Planner
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- 4.Grant, M., Boyd, S.: CVX: Matlab software for disciplined convex programming, version 1.21 (May 2010), http://cvxr.com/cvx
- 7.Lochmatter, T., Roduit, P., Cianci, C., Correll, N., Jacot, J., Martinoli, A.: Swistrack - a flexible open source tracking software for multi-agent systems. In: Proc. of the 2008 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS 2008), pp. 4004–4010 (2008)Google Scholar
- 9.Matthey, L., Berman, S., Kumar, V.: Stochastic strategies for a swarm robotic assembly system. In: Proc. of the 2009 IEEE Int. Conf. on Robotics and Automation (ICRA 2009), pp. 1953–1958 (May 2009)Google Scholar
- 10.Mermoud, G., Brugger, J., Martinoli, A.: Towards multi-level modeling of self-assembling intelligent micro-systems. In: Proc. of the 8th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS 2009), vol. 1, pp. 89–96 (May 2009)Google Scholar
- 11.Mermoud, G., Matthey, L., Evans, W., Martinoli, A.: Aggregation-mediated collective perception and action in a swarm of miniature robots. In: Luck, M., Sen, S., van der Hoewk, W., Kaminka, G. (eds.) Proc. of the 9th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS 2010), Toronto, Canada, pp. 599–606 (May 2010)Google Scholar