Practical hardware for evolvable robots

Frontiers in Robotics and AI

Robotics and AI

Alan F. Winfield¹  Matthew F. Hale¹  Matteo De Carlo²  Agoston E. Eiben²  Jon Timmis³  Emma Hart⁴  Léni K. Le Goff⁴  Edgar Buchanan⁵  Mike Angus⁵  Robert Woolley⁵  Andy M. Tyrrell⁵ 

[1] Bristol Robotics Laboratory, University of the West of England, Bristol, United Kingdom;Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, Netherlands;School of Computer Science, University of Sunderland, Sunderland, United Kingdom;School of Computing, Edinburgh Napier University, Edinburgh, United Kingdom;School of Physics, Engineering and Technology, University of York, York, United Kingdom;

关键词: evolutionary robotics;    hardware design;    modular robots;    hardware constraints;    autonomous robot fabrication;    robot manufacturability;   

DOI  :  10.3389/frobt.2023.1206055

 received in 2023-04-14, accepted in 2023-08-07,  发布年份 2023

来源: Frontiers

【 摘 要 】

The evolutionary robotics field offers the possibility of autonomously generating robots that are adapted to desired tasks by iteratively optimising across successive generations of robots with varying configurations until a high-performing candidate is found. The prohibitive time and cost of actually building this many robots means that most evolutionary robotics work is conducted in simulation, but to apply evolved robots to real-world problems, they must be implemented in hardware, which brings new challenges. This paper explores in detail the design of an example system for realising diverse evolved robot bodies, and specifically how this interacts with the evolutionary process. We discover that every aspect of the hardware implementation introduces constraints that change the evolutionary space, and exploring this interplay between hardware constraints and evolution is the key contribution of this paper. In simulation, any robot that can be defined by a suitable genetic representation can be implemented and evaluated, but in hardware, real-world limitations like manufacturing/assembly constraints and electrical power delivery mean that many of these robots cannot be built, or will malfunction in operation. This presents the novel challenge of how to constrain an evolutionary process within the space of evolvable phenotypes to only those regions that are practically feasible: the viable phenotype space. Methods of phenotype filtering and repair were introduced to address this, and found to degrade the diversity of the robot population and impede traversal of the exploration space. Furthermore, the degrees of freedom permitted by the hardware constraints were found to be poorly matched to the types of morphological variation that would be the most useful in the target environment. Consequently, the ability of the evolutionary process to generate robots with effective adaptations was greatly reduced. The conclusions from this are twofold. 1) Designing a hardware platform for evolving robots requires different thinking, in which all design decisions should be made with reference to their impact on the viable phenotype space. 2) It is insufficient to just evolve robots in simulation without detailed consideration of how they will be implemented in hardware, because the hardware constraints have a profound impact on the evolutionary space.

【 授权许可】

Unknown   
Copyright © 2023 Angus, Buchanan, Le Goff, Hart, Eiben, De Carlo, Winfield, Hale, Woolley, Timmis and Tyrrell.