Max Robotics — Global Service Robot Directory + US Certification

About

Giles Mayley is a researcher specializing in evolutionary robotics and multi-robot systems, with a particular focus on the automatic design of controllers for autonomous robot teams. His most significant contributions center on applying artificial evolution — specifically neural network-based approaches — to develop coordinated behaviors in homogeneous groups of physical robots, a domain that was largely unexplored when single-robot systems dominated the field. Mayley's most impactful work, "Evolving controllers for a homogeneous system of physical robots" (2003), has garnered 152 citations and demonstrates how evolutionary algorithms can produce sophisticated cooperative behaviors — including formation movement and implicit role-allocation — using only minimal infrared sensor inputs. This research was notable for its emphasis on real hardware rather than simulation alone, adding significant practical credibility to his findings. Across his body of work, Mayley tackled fundamental challenges in emergent teamwork, showing how robots could coordinate from random starting positions without explicit communication or pre-programmed roles. His cumulative contributions helped establish a research foundation for evolutionary approaches to multi-robot cooperation, influencing subsequent generations of researchers working at the intersection of evolutionary computation, swarm robotics, and autonomous systems.