Abstract
This paper presents a plant root behavior-based approach to defining the control architecture of a plant-root-inspired robot, which is composed of three root-agents for nutrient uptake and one shoot-agent for nutrient redistribution. By taking inspiration and extracting key principles from the uptake of nutrient, movements and communication strategies adopted by plant roots, we developed an uptake–kinetics feedback control for the robotic roots. Exploiting the proposed control, each root is able to regulate the growth direction, towards the nutrients that are most needed, and to adjust nutrient uptake, by decreasing the absorption rate of the most plentiful one. Results from computer simulations and implementation of the proposed control on the robotic platform, Plantoid, demonstrate an emergent swarming behavior aimed at optimizing the internal equilibrium among nutrients through the self-organization of the roots. Plant wellness is improved by dynamically adjusting nutrients priorities only according to local information without the need of a centralized unit delegated for wellness monitoring and task allocation among the agents. Thus, the root-agents can ideally and autonomously grow at the best speed, exploiting nutrient distribution and improving performance, in terms of exploration capabilities and exploitation of resources, with respect to the tropism-inspired control previously proposed by the same authors.
Highlights
A decentralized control system is a system in which the components act on the basis of local information when accomplishing global tasks
In which a and b are two constants, θ is the tolerance angle and β is the inclination of the tip from the gravity. a, b and θ are fixed parameters
Plant roots are proposed as a source of inspiration for the design and architecture of robotic control
Summary
A decentralized control system is a system in which the components act on the basis of local information when accomplishing global tasks. In such systems, the collaborative behavior emerges from independent local decisions without the need for centralized processing [1]. The collaborative behavior emerges from independent local decisions without the need for centralized processing [1] This definition is intrinsically linked to the idea of self-organization. Many natural systems have been studied in terms of their ability to perform complex tasks without a centralized control but due to simple rules followed by many distributed agents with communication capabilities [2]. Systems that have no nervous system are considered, such as bacteria that organize themselves in order to maximize nutrient availability [5]
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