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Bio-inspired design of hard-bodied mobile robots based on arthropod morphologies: a 10 year systematic review and bibliometric analysis.

José CornejoJesus Enrique Sierra-GarciaFrancisco Javier Gomez-GilAlfredo WeitzenfeldFlor Edith AcevedoIgnacio EscalanteErnesto RecueroIngo S Wehrtmann
Published in: Bioinspiration & biomimetics (2024)
This research presents a 10-year systematic review based on bibliometric analysis of the bio-inspired design of hard-bodied mobile robot mechatronic systems considering the anatomy of arthropods. These are the most diverse group of animals whose flexible biomechanics and adaptable morphology, thus, it can inspire robot development. Papers were reviewed from two international databases (Scopus and Web of Science) and one platform (Aerospace Research Central), then they were classified according to: Year of publication (January 2013 to April 2023), arthropod group, published journal, conference proceedings, editorial publisher, research teams, robot classification according to the name of arthropod, limb's locomotion support, number of legs/arms, number of legs/body segments, limb's degrees of freedom, mechanical actuation type, modular system, and environment adaptation. During the screening, more than 33 000 works were analyzed. Finally, a total of 174 studies (90 journal-type, 84 conference-type) were selected for in-depth study: Insecta-hexapods (53.8%), Arachnida-octopods (20.7%), Crustacea-decapods (16.1%), and Myriapoda-centipedes and millipedes (9.2%). The study reveals that the most active editorials are the Institute of Electrical and Electronics Engineers Inc., Springer, MDPI, and Elsevier, while the most influential researchers are located in the USA, China, Singapore, and Japan. Most works pertained to spiders, crabs, caterpillars, cockroaches, and centipedes. We conclude that 'arthrobotics' research, which merges arthropods and robotics, is constantly growing and includes a high number of relevant studies with findings that can inspire new methods to design biomechatronic systems.
Keyphrases
  • systematic review
  • meta analyses
  • machine learning
  • public health
  • randomized controlled trial
  • deep learning
  • optical coherence tomography
  • artificial intelligence
  • case control