Vol. 3 No. 1 (2023): African Journal of Artificial Intelligence and Sustainable Development
Articles

Evolutionary Morphological Robotics: Exploring morphological evolution techniques for designing robots with adaptive and versatile physical structures

Dr. Ingrid Gustavsson
Associate Professor of Human-Computer Interaction, University of Gothenburg, Sweden
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Published 14-05-2023

Keywords

  • Evolutionary Morphological Robotics,
  • Evolutionary Computation,
  • Robot Morphology

How to Cite

[1]
Dr. Ingrid Gustavsson, “Evolutionary Morphological Robotics: Exploring morphological evolution techniques for designing robots with adaptive and versatile physical structures”, African J. of Artificial Int. and Sust. Dev., vol. 3, no. 1, pp. 112–119, May 2023, Accessed: Jul. 01, 2024. [Online]. Available: https://africansciencegroup.com/index.php/AJAISD/article/view/65

Abstract

Evolutionary Morphological Robotics (EMR) is an emerging field that combines evolutionary computation and robotics to design robots with adaptive and versatile physical structures. This paper presents an overview of EMR techniques, focusing on how they can be used to create robots that can adapt to different environments and tasks. We discuss the key concepts and methodologies of EMR, including the use of evolutionary algorithms to optimize robot morphology, the integration of sensory feedback for adaptive behavior, and the challenges and future directions of the field. Through case studies and examples, we demonstrate the potential of EMR in creating robots that are capable of robust and flexible performance in complex and dynamic environments.

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References

  1. Tatineni, Sumanth. "Exploring the Challenges and Prospects in Data Science and Information Professions." International Journal of Management (IJM) 12.2 (2021): 1009-1014.
  2. Gudala, Leeladhar, Mahammad Shaik, and Srinivasan Venkataramanan. "Leveraging Machine Learning for Enhanced Threat Detection and Response in Zero Trust Security Frameworks: An Exploration of Real-Time Anomaly Identification and Adaptive Mitigation Strategies." Journal of Artificial Intelligence Research 1.2 (2021): 19-45.
  3. Tatineni, Sumanth. "Compliance and Audit Challenges in DevOps: A Security Perspective." International Research Journal of Modernization in Engineering Technology and Science 5.10 (2023): 1306-1316.