Navigating multi-robot systems in complex terrains has always been a challenging task. This is due to the inherent limitations of traditional robots in collision avoidance, adaptation to unknown environments, and sustained energy efficiency. In order to overcome these limitations, this research proposes a solution by integrating living insects with miniature electronic controllers to enable robotic-like programmable control, and proposing a novel control algorithm for swarming. Although these creatures, called cyborg insects, have the ability to instinctively avoid collisions with neighbors and obstacles while adapting to complex terrains, there is a lack of literature on the control of multi-cyborg systems. This research gap is due to the difficulty in coordinating the movements of a cyborg system under the presence of insects' inherent individual variability in their reactions to control input. In response to this issue, we propose a novel swarm navigation algorithm addressing these challenges. The effectiveness of the algorithm is demonstrated through an experimental validation in which a cyborg swarm was successfully navigated through an unknown sandy field with obstacles and hills. This research contributes to the domain of swarm robotics and showcases the potential of integrating biological organisms with robotics and control theory to create more intelligent autonomous systems with real-world applications.

翻译：在复杂地形中导航多机器人系统始终是一项具有挑战性的任务。这源于传统机器人在避障、适应未知环境以及持续能源效率方面固有的局限性。为克服这些限制，本研究提出了一种解决方案，通过将活体昆虫与微型电子控制器集成以实现类似机器人的可编程控制，并提出了一种新颖的群体控制算法。尽管这些被称为半机械昆虫的生物具备本能避让相邻个体及障碍物、同时适应复杂地形的能力，但关于多半机械系统控制的文献尚属空白。这一研究缺口源于：在昆虫对控制输入存在固有个体反应差异的情况下，协调半机械系统运动存在困难。针对这一问题，我们提出了一种新型群体导航算法以应对这些挑战。通过在布满障碍物与丘陵的未知沙地环境中成功引导半机械虫群完成导航的实验验证，证明了该算法的有效性。本研究为群体机器人学领域做出了贡献，并展示了将生物有机体与机器人学及控制理论相结合，以创造更具实际应用价值的智能自主系统的潜力。