Challenges and Opportunities of Evolutionary Robotics

Robotic hardware designs are becoming more complex as the variety and number of on-board sensors increase and as greater computational power is provided in ever-smaller packages on-board robots. These advances in hardware, however, do not automatically translate into better software for controlling complex robots. Evolutionary techniques hold the potential to solve many difficult problems in robotics which defy simple conventional approaches, but present many challenges as well. Numerous disciplines including artificial life, cognitive science and neural networks, rule-based systems, behavior-based control, genetic algorithms and other forms of evolutionary computation have contributed to shaping the current state of evolutionary robotics. This paper provides an overview of developments in the emerging field of evolutionary robotics, and discusses some of the opportunities and challenges which currently face practitioners in the field.

• Publication year

  2007

• Venue

  arXiv.org

• Publication date

  2007-06-04

• Fields of study

  Computer Science, Engineering

• Identifiers
  arXiv 0706.0457
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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