Miguel Duarte

TL;DR: This paper demonstrates for the first time a swarm robotics system with evolved control successfully operating in a real and uncontrolled environment and validates that the evolved controllers display key properties of swarm intelligence-based control, namely scalability, flexibility, and robustness on the real swarm.

TL;DR: The benefits and challenges of simulation-based evolution and subsequent deployment of controllers versus evolution on real robotic hardware are analyzed and the role of genomic encoding and genotype-phenotype mapping in the evolution of controllers for complex tasks is addressed.

TL;DR: The evolutionary repertoire-based control (EvoRBC) approach, which divides the synthesis of control into two steps: 1) the evolution of a repertoire of locomotion primitives using a quality diversity algorithm and 2) a high-level arbitrator that leverages the locomotionPrimitives in the repertoire to solve a given task.

TL;DR: The results show that swarm robotics systems are suited for environmental monitoring tasks by efficiently covering a target area, allowing for redundancy in the data collection process, and tolerating individual robot faults.

TL;DR: JBotEvolver as discussed by the authors is a Java-based simulation platform for research and education in evolutionary robotics (ER), which has been used in a number of previous ER studies of our research group.