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Real-World Robot Evolution: Why Would it (not) Work?
- Source :
- Eiben, A E 2021, ' Real-World Robot Evolution : Why Would it (not) Work? ', Frontiers in Robotics and AI, vol. 8, 696452 . https://doi.org/10.3389/frobt.2021.696452, Frontiers in Robotics and AI, Frontiers in Robotics and AI, Vol 8 (2021)
- Publication Year :
- 2021
- Publisher :
- Frontiers Media SA, 2021.
-
Abstract
- © Copyright © 2021 Eiben.This paper takes a critical look at the concept of real-world robot evolution discussing specific challenges for making it practicable. After a brief review of the state of the art several enablers are discussed in detail. It is noted that sample efficient evolution is one of the key prerequisites and there are various promising directions towards this in different stages of maturity, including learning as part of the evolutionary system, genotype filtering, and hybridizing real-world evolution with simulations in a new way. Furthermore, it is emphasized that an evolutionary system that works in the real world needs robots that work in the real world. Obvious as it may seem, to achieve this significant complexification of the robots and their tasks is needed compared to the current practice. Finally, the importance of not only building but also understanding evolving robot systems is emphasised, stating that in order to have the technology work we also need the science behind it.
- Subjects :
- 0209 industrial biotechnology
Computer science
Mini Review
Evolutionary robotics
Sample (statistics)
02 engineering and technology
020901 industrial engineering & automation
reality gap
Artificial Intelligence
Order (exchange)
TJ1-1570
Mechanical engineering and machinery
learning and evolution
triangle of life framework
Robotics and AI
QA75.5-76.95
021001 nanoscience & nanotechnology
Maturity (finance)
Data science
evolution of things
Computer Science Applications
Robotic systems
Work (electrical)
Electronic computers. Computer science
Key (cryptography)
Robot
simulations
0210 nano-technology
evolutionary robotics
Subjects
Details
- ISSN :
- 22969144
- Volume :
- 8
- Database :
- OpenAIRE
- Journal :
- Frontiers in Robotics and AI
- Accession number :
- edsair.doi.dedup.....392b136fe35a6872a2bd866032bab756
- Full Text :
- https://doi.org/10.3389/frobt.2021.696452