Abstract
Previous work has shown that virtual hormone systems can be engineered to arbitrate swarms of robots between sets of behaviours. These virtual hormones act similarly to their natural counterparts, providing a method of online, reactive adaptation. It is yet to be shown how virtual hormone systems could be used when a robotic swarm has a large variety of task types to execute. This paper details work that demonstrates the viability of a collection of virtual hormones that can be used to regulate and adapt a swarm over time, in response to different environments and tasks. Specifically, the paper examines a new method of hormone speed control for energy efficiency and combines it with two existing systems controlling environmental preference as well as a selection of behaviours that produce an effective foraging swarm. Experiments confirm the effectiveness of the combined system, showing that a swarm of robots equipped with multiple virtual hormones can forage efficiently to a specified item demand within an allotted period of time.
Highlights
In nature, hormones provide an adaptation technique that cues behavioural change through chemical processing
In the context of robotics, previous work has shown that virtual hormones can be engineered to control, arbitrate and adapt swarms of robots amongst a small set of behaviours in a similar manner to the examples seen in nature [4,5,6]
It is yet to be shown how hormone systems could be used when a large array of behaviours and task types are available to a swarm
Summary
Hormones provide an adaptation technique that cues behavioural change through chemical processing. The work in this paper combines these applications to create an energy efficient foraging swarm regulated by numerous, simultaneously functioning hormones. This will focus on the need for adaptive motor speeds and their implementation. Creating a system with 6 or more simultaneously acting virtual hormones in each member of the swarm, depending on the number of environments available to the swarm The implementation of this complex virtual hormone system will be effective for live adaptation and produce significant improvements to energy efficiency in foraging examples over individual hormone systems.
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