Editorial: Focus on methods: neural algorithms for bio-inspired robotics

• Published in: Frontiers in neurorobotics Vol. 17; p. 1250645
• Main Authors: Patanè, Luca, Zhao, Guoping
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Research Foundation 25.07.2023; Frontiers Media S.A
• Subjects: Algorithms; bio-robotics; biological signal processing; Brain research; Conflicts of interest; Decision making; intelligent machines; Locomotion; Machine learning; Nervous system; neural control; Neural networks; Neuroscience; Neurosciences; Robotics; Robots; Signal processing; bio-robotics; intelligent machines; neural control; biological signal processing; machine learning
• ISSN: 1662-5218; 1662-5218
• DOI: 10.3389/fnbot.2023.1250645

Introduction Bio-inspired robotics aims to develop robotic systems that mimic or are inspired by biological systems and processes. In recent decades, research has gained deep insights into biological systems, from cell biology to physiology, biomechanics, and locomotion (Meyer and Guillot, 2008; Mazzolai et al., 2020; Valero-Cuevas and Erwin, 2022). A recent review of insect-inspired robots shows the useful influence of biological systems at different levels of robot design, from the mechanical part to the locomotion control system to the sophisticated capabilities involving decision-making processes (Manoonpong et al., 2021).