Broadening applicability of swarm-robotic foraging through constraint relaxation
| Autor: | Maria Gini, John Harwell |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
0209 industrial biotechnology
Mathematical optimization Computer science Foraging Swarm robotics Swarm behaviour 02 engineering and technology Task (project management) 020901 industrial engineering & automation Robustness (computer science) 0202 electrical engineering electronic engineering information engineering Task analysis Robot A priori and a posteriori 020201 artificial intelligence & image processing |
| Zdroj: | SIMPAR |
| Popis: | Swarm robotics (SR) offers promising solutions to real-world problems that can be modeled as foraging tasks, e.g. disaster/trash cleanup or object gathering for construction. Yet current SR foraging approaches make limiting assumptions that restrict their applicability to selected real-world environments. We propose an improved self-organized task allocation method based on task partitioning that removes restrictions such as: (1) a priori knowledge of foraging environment, and (2) strict limitations on intermediate drop/pickup site behavior. With experiments in simulation, we show that under the proposed constraint relaxation, our approach still provides performance increases when compared to an unpartitioned strategy within some combinations of swarm sizes, robot capabilities, and environmental conditions. This work broadens the applicability of SR foraging approaches, showing that they can be effective under ideal conditions while continuing to perform robustly in more volatile/challenging environments. |
| Databáze: | OpenAIRE |
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