Cyborg Moth Flight Control Based on Fuzzy Deep Learning

A Navigation Algorithm to Enable Sustainable Control of Insect-Computer Hybrid Robot with Stimulus Signal Regulator and Habituation-Breaking Function

The insect-computer hybrid soft robots are receiving increasing attention due to their excellent motor capabilities, small size, and low power consumption. However, the effective control of insects is limited to minutes since the response from insects is reduced as the number of stimulus signal increase. This phenomenon is known as habituation, which causes the loss of control of robots and hinders their application in practical tasks such as search and rescue missions that require several hours. It has been shown that constantly switching the pattern of stimulus signals can slow down the onset of habituation. Moreover, when habituation occurs, applying a different stimulus signal can break the habituation. Based on this, we have designed a navigation algorithm that can extend the control time of insects to several hours. The algorithm is composed of a stimulation decision-making core responsible for deciding on the type of stimulus signal (left, right, acceleration), a stimulation parameters adjustment (SPA) core responsible for adjusting the stimulus signal voltage constantly to delay the occurrence of habituation, and a reactivation function (RF), as a different stimulus signal from the normal stimulus signal, is used to break insects' habituation to the normal stimulus signal. Experiments have shown that our SPA regulator and RF can significantly extend the control time of insects. Navigation experiments demonstrating effective control of the insects for up to 3 h verified the effectiveness of the navigation algorithm, which strikes a balance between control accuracy and control time.

A Review of Energy Supply for Biomachine Hybrid Robots

Biomachine hybrid robots have been proposed for important scenarios, such as wilderness rescue, ecological monitoring, and hazardous area surveying. The energy supply unit used to power the control backpack carried by these robots determines their future development and practical application. Current energy supply devices for control backpacks are mainly chemical batteries. To achieve self-powered devices, researchers have developed solar energy, bioenergy, biothermal energy, and biovibration energy harvesters. This review provides an overview of research in the development of chemical batteries and self-powered devices for biomachine hybrid robots. Various batteries for different biocarriers and the entry points for the design of self-powered devices are outlined in detail. Finally, an overview of the future challenges and possible directions for the development of energy supply devices used to biomachine hybrid robots is provided.