Insect-Inspired Robots: Bridging Biological and Artificial Systems - Archive ouverte HAL
Article Dans Une Revue Sensors Année : 2021

Insect-Inspired Robots: Bridging Biological and Artificial Systems

Résumé

This review article aims to address common research questions in hexapod robotics. How can we build intelligent autonomous hexapod robots that can exploit their biomechanics, morphology, and computational systems, to achieve autonomy, adaptability, and energy efficiency comparable to small living creatures, such as insects? Are insects good models for building such intelligent hexapod robots because they are the only animals with six legs? This review article is divided into three main sections to address these questions, as well as to assist roboticists in identifying relevant and future directions in the field of hexapod robotics over the next decade. After an introduction in section (1), the sections will respectively cover the following three key areas: (2) biomechanics focused on the design of smart legs; (3) locomotion control; and (4) high-level cognition control. These interconnected and interdependent areas are all crucial to improving the level of performance of hexapod robotics in terms of energy efficiency, terrain adaptability, autonomy, and operational range. We will also discuss how the next generation of bioroboticists will be able to transfer knowledge from biology to robotics and vice versa.
Fichier principal
Vignette du fichier
2021-Manoopong et al. Insect-Inspired Robots Bridging Biological and Artificial Systems- Review MDPI sensors-21-07609.pdf (13.3 Mo) Télécharger le fichier
Origine Fichiers éditeurs autorisés sur une archive ouverte

Dates et versions

hal-03430897 , version 1 (16-11-2021)

Licence

Identifiants

Citer

Poramate Manoonpong, Luca Patanè, Xiaofeng Xiong, Ilya Brodoline, Julien Dupeyroux, et al.. Insect-Inspired Robots: Bridging Biological and Artificial Systems. Sensors, 2021, 21 (22), pp.7609. ⟨10.3390/s21227609⟩. ⟨hal-03430897⟩
93 Consultations
175 Téléchargements

Altmetric

Partager

More