Distributed Adaptive Control: An Ideal Cognitive Architecture Candidate for Managing a Robotic Recycling Plant

Abstract

In the past decade, society has experienced notable growth in a variety of technological areas. However, the Fourth Industrial Revolution has not been embraced yet. Industry 4.0 imposes several challenges which include the necessity of new architectural models to tackle the uncertainty that open environments represent to cyber-physical systems (CPS). Waste Electrical and Electronic Equipment (WEEE) recycling plants stand for one of such open environments. Here, CPSs must work harmoniously in a changing environment, interacting with similar and not so similar CPSs, and adaptively collaborating with human workers. In this paper, we support the Distributed Adaptive Control (DAC) theory as a suitable Cognitive Architecture for managing a recycling plant. Specifically, a recursive implementation of DAC (between both singleagent and large-scale levels) is proposed to meet the expected demands of the European Project HR-Recycler. Additionally, with the aim of having a realistic benchmark for future implementations of the recursive DAC, a micro-recycling plant prototype is presented.

Drive competition underlies effective allostatic orchestration

“…Secondly, general-purpose robot instantiations can benefit greatly from the self-regulatory principles described here. Previous works elaborated on how a multi-agent robotic recycling plant can implement homeostatic and allostatic principles to self-organize at both single-agent and large-scale levels (Rosado and Verschure, 2020). Similar architectures can be designed and implemented to advance a variety of scenarios where robot autonomy is key such as robot delivery or space exploration.…”