Environment-Adaptive Navigation Method for Biorobots Enhanced by the Innate Nature of Insects

Biorobots involve embedding artificial components into a living insect to transform it into a controllable robot, which comes with the advantages of low energy consumption, quietness, and flexibility. However, no models have yet been developed to describe the randomness-filled motions of biorobots, and their unique biological properties are also underutilized. In this work, the locomotion responses of a biorobot to electrical stimuli were summarized. The constant-current signal was found to have a higher capacity for sustained stimuli than existing methods. The joint influence of wall and current factors on cockroach behavior was explored to establish an environment-adaptive control model describing their locomotion. This model was then used to propose an navigation method enhanced by the inherent nature of a biorobot. In an indoor scenario, the proposed method achieved a success rate of 78.6% with minimal runtime and stimulus number while the control group using conventional navigation methods achieved a success rate of 30%, with two or three times the runtime and stimulus number. Compared with other approaches, the proposed method facilitates high-precision and long-range navigation with a short navigation time and very low control costs. Note to Practitioners—Biorobots are novel types of robots that transform live insects into ingenious devices. They have great potential in narrow, special scenarios. However, current biorobots face the problems of insufficient endurance and low control accuracy in their applications. In this study, we proposed a constant-current drive method that can effectively increase the endurance of biorobots, and established a kinematic model (probably the first) covering its various stimuli-stages. The model used a machine learning approach and considered the significant environment factor. Based on the model, this study proposed an biorobot-adaption navigation algorithm. The algorithm exploited the nature of insects and allow the biorobot to complete navigation with high control indexes. The result demonstrates that the idea of insect-nature-utilization is feasible in biorobot control. It is possible to obtain the result exceeding current studies without complex method under this idea. In future research, we will follow this idea and try to use more biorobots in more complex scenarios to accomplish specific tasks.