Steering self-organized robot flocks through externally guided individuals

Date

2010-09-01

Author

Celikkanat, Hande
Şahin, Erol

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In this paper, we study how a self-organized mobile robot flock can be steered toward a desired direction through externally guiding some of its members. Specifically, we propose a behavior by extending a previously developed flocking behavior to steer self-organized flocks in both physical and simulated mobile robots. We quantitatively measure the performance of the proposed behavior under different parameter settings using three metrics, namely, (1) the mutual information metric, adopted from Information Theory, to measure the information shared between the individuals during steering, (2) the accuracy metric from directional statistics to measure the angular deviation of the direction of the flock from the desired direction, and (3) the ratio of the largest aggregate to the whole flock and the ratio of informed individuals remaining with the largest aggregate, as a metric of flock cohesion. We conducted a systematic set of experiments using both physical and simulated robots, analyzed the transient and steady-state characteristics of steered flocking, and evaluate the parameter conditions under which a swarm can be successfully steered. We show that the experimental results are qualitatively in accordance with the ones that were predicted in Couzin et al. model (Nature, 433:513-516, 2005) and relate the quantitative differences to the differences between the models.

Subject Keywords

Software, Artificial Intelligence

URI

https://hdl.handle.net/11511/40754

Journal

NEURAL COMPUTING & APPLICATIONS

DOI

https://doi.org/10.1007/s00521-010-0355-y

Collections

Department of Computer Engineering, Article

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Citation Formats

H. Celikkanat and E. Şahin, “Steering self-organized robot flocks through externally guided individuals,” NEURAL COMPUTING & APPLICATIONS, pp. 849–865, 2010, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/40754.