Progress and Prospects of Evolutionary Robotics

A special issue of Robotics (ISSN 2218-6581).

Deadline for manuscript submissions: 31 January 2025 | Viewed by 1334

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School of Physics, Engineering and Technology, University of York, Heslington, UK
Interests: evolutionary robotics; bio-Inspired computing and AI; evolutionary algorithms; evolutionary computing
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Special Issue Information

Dear Colleagues,

Traditional ways of designing robots have shown success mainly in controlled and well-understood environments. However, as applications for robots grow, the environments they will operate in become less controllable, and the development of new robot materials (soft robotics, for example) make these traditional design methods less applicable. One area that is becoming more popular for robot design is Evolutionary Robotics. The majority of work in Evolutionary Robotics has either been achieved in simulation or studies using evolution on physical robots using fixed robotic hardware. The evolution of morphologies (and control systems) has been addressed in artificial life in simulated worlds with virtual creatures. Recent work has addressed the evolution of morphologies in novel substrates and soft materials, but in both cases, evolution took place in simulation and only the final morphologies were physically constructed post evolution. In the majority of work in Evolutionary Robotics to date, simulated and real trials are weakly linked and evolution in simulation is the primary process. A major question that still remains is how to evolve complete robots (bodies and brains) in real time and real space in a rich morphological space that enables closed-loop control by incorporating a range of sensors, multiple type of actuator and free-form skeletons. This would move the state of the art by concurrently running virtual and physical evolution integrated with bi-directional migration and cross-fertilisation between virtual and physical individuals.

This Special Issue invites the submission of papers that present new methods, approaches, designs, concepts and software tools for Evolutionary Robotics. Potential topics include, but are not limited to, the following: novel methods for simultaneous evolution of morphology and/or control, novel methods for facilitating learning and/or adaptation during lifetime, robot evolution in hardware and evolution of morphologies using novel materials.

Prof. Dr. Andy Tyrrell
Guest Editor

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Keywords

  • evolution
  • morphology
  • control
  • learning
  • adaptation
  • populations
  • intelligence
  • hardware
  • reality gap

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Published Papers (1 paper)

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19 pages, 8123 KiB  
Article
Towards a Unified Framework for Software-Hardware Integration in Evolutionary Robotics
by Edgar Buchanan, Léni K. Le Goff, Matthew F. Hale, Emma Hart, Agoston E. Eiben, Matteo De Carlo, Mike Angus, Robert Woolley, Jon Timmis, Alan F. Winfield and Andy M. Tyrrell
Robotics 2024, 13(11), 157; https://doi.org/10.3390/robotics13110157 - 25 Oct 2024
Viewed by 1010
Abstract
The discrepancy between simulated and hardware experiments, the reality gap, is a challenge in evolutionary robotics. While strategies have been proposed to address this gap in fixed-body robots, they are not viable when dealing with populations and generations where the body is in [...] Read more.
The discrepancy between simulated and hardware experiments, the reality gap, is a challenge in evolutionary robotics. While strategies have been proposed to address this gap in fixed-body robots, they are not viable when dealing with populations and generations where the body is in constant change. The continual evolution of body designs necessitates the manufacturing of new robotic structures, a process that can be time-consuming if carried out manually. Moreover, the increased manufacturing time not only prolongs hardware experimental durations but also disrupts the synergy between hardware and simulated experiments. Failure to effectively manage these challenges could impede the implementation of evolutionary robotics in real-life environments. The Autonomous Robot Evolution project presents a framework to tackle these challenges through a case study. This paper describes the main three contributions of this work: Firstly, it analyses the different reality gap experienced by each different robot or the heterogenous reality gap. Secondly, it emphasizes the importance of automation in robot manufacturing. And thirdly, it highlights the necessity of a framework to orchestrate the synergy between simulated and hardware experiments. In the long term, integrating these contributions into evolutionary robotics is envisioned to enable the continuous production of robots in real-world environments. Full article
(This article belongs to the Special Issue Progress and Prospects of Evolutionary Robotics)
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