论文标题

陆生昆虫造成的混合系统的有效自主导航

Efficient Autonomous Navigation for Terrestrial Insect-Machine Hybrid Systems

论文作者

Nguyen, Huu Duoc, Dung, Van Than, Sato, Hirotaka, Vo-Doan, T. Thang

论文摘要

虽然生物启发和仿生系统从活物质中汲取灵感,但生物杂种系统将它们与合成设备融合在一起,从而允许在单个实体内剥削有机和人工优势。在为非结构化领土导航提供的厘米尺寸的移动机器人的挑战性开发中,生物杂种系统作为潜在的解决方案,以陆生昆虫造成的杂种系统形式,这些杂种杂种系统是活着的卧床昆虫和微型电子设备的融合。尽管可以通过人工电刺激故意控制其操纵,但这些混合系统仍然继承了昆虫出色的运动技能,这是由复杂的中枢神经系统和各种感觉器官精心策划的,偏爱在复杂地形中的动作。但是,这些混合系统的有效自主导航具有挑战性。优化各个昆虫的刺激参数的努力限制了导航控制的可靠性和准确性。这项研究通过实施反馈控制系统,洞悉基于生存的黑暗甲虫的昆虫机器混合动力系统的可调导航控制系统,从而克服了这一问题。通过推力控制器的加速度和用于转动的比例控制器,系统根据混合机器人的瞬时状态调节刺激参数。尽管该系统可以为遵循路径的导航提供〜71%的总体成功率,但对控制参数进行微调可以进一步提高结果的可靠性和精度,分别达到〜94%的成功率和〜1/2的身体长度精度。反馈控制系统的这种可调节性能为昆虫造影混合系统的导航应用提供了灵活性。

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 view of 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.

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