A high-performance millirobot for swarm-behaviour studies: Swarm-topology estimation
Justin Y. Kim, Zendai Kashino, Laura Marcela Pineros, Sayeh Bayat, Tyler Colaco, Goldie Nejat, B. Benhabib
- Year
- 2019
- Citations
- 8
- Access
- Open access
Abstract
In this article, we present a novel high-performance millirobot ( milli- robot- Toronto), designed to allow for the testing of complex swarm-behaviours, including human–swarm interaction. milli- robot- Toronto, built only with off-the-shelf components, has locomotion, processing and sensing capabilities that significantly improve upon existing designs, while maintaining one of the smallest footprints among current millirobots. As complementary software to this hardware development, herein, we also present a new global swarm-topology estimation algorithm. The method is novel in that it uniquely fuses incomplete location data collected by the individual robots in a distributed manner to optimally estimate the topology of the overall swarm using a centralized computer. It is a generalized technique usable by any swarm comprising robots capable of collecting location estimates of neighbouring robots. Numerous experiments, evaluating the performance of milli- robot- Toronto and the proposed optimal swarm-topology estimation algorithm, are also included.
Keywords
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