Efficient autonomous navigation for terrestrial insect-machine hybrid systems

• Main Authors: Nguyen, Huu Duoc, Dung, Van Than, Sato, Hirotaka, Vo-Doan, T. Thang
• Other Authors: School of Mechanical and Aerospace Engineering
• Format: Article
• Language: English
• Published: 2023
• Subjects: Engineering::Mechanical engineering; Biohybrid Systems; Zophobas Morio
• Online Access: https://hdl.handle.net/10356/170441
• Institution: Nanyang Technological University

While bio-inspired and biomimetic systems draw inspiration from living materials, biohybrid systems incorporate them with synthetic devices, allowing the exploitation of both organic and artificial advantages inside a single entity. In the challenging development of centimeter-scaled mobile robots serving unstructured territory navigations, biohybrid systems appear as a potential solution in the forms of terrestrial insect-machine hybrid systems, which are the fusion of living ambulatory insects and miniature electronic devices. Although their maneuver can be deliberately controlled via artificial electrical stimulation, these hybrid systems still inherit the insects’ outstanding locomotory skills, orchestrated by a sophisticated central nervous system and various sensory organs, favoring their maneuvers in complex terrains. However, efficient autonomous navigation of these hybrid systems is challenging. The struggle to optimize the stimulation parameters for individual insects limits the reliability and accuracy of navigation control. This study overcomes this problem by implementing a feedback control system with an insight into tunable navigation control for an insect-machine hybrid system based on a living darkling beetle. Via a thrust controller for acceleration and a proportional controller for turning, the system regulates the stimulation parameters based on the instantaneous status of the hybrid robot. While the system can provide an overall success rate of ~ 71% for path-following navigations, fine tuning its control parameters could further improve the outcome’s reliability and precision to up to ∼ 94% success rate and ∼ 1/2 body length accuracy, respectively. Such tunable performance of the feedback control system provides flexibility to navigation applications of insect-machine hybrid systems.