Cyborg Moth Flight Control Based on Fuzzy Deep Learning

Cyborg insect control methods can be divided into invasive methods and noninvasive methods. Compared to invasive methods, noninvasive methods are much easier to implement, but they are sensitive to complex and highly uncertain environments, for which classical control methods often have low control accuracy. In this paper, we present a noninvasive approach for cyborg moths stimulated by noninvasive ultraviolet (UV) rays. We propose a fuzzy deep learning method for cyborg moth flight control, which consists of a Behavior Learner and a Control Learner. The Behavior Learner is further divided into three hierarchies for learning the species’ common behaviors, group-specific behaviors, and individual-specific behaviors step by step to produce the expected flight parameters. The Control Learner learns how to set UV ray stimulation to make a moth exhibit the expected flight behaviors. Both the Control Learner and Behavior Learner (including its sub-learners) are constructed using a Pythagorean fuzzy denoising autoencoder model. Experimental results demonstrate that the proposed approach achieves significant performance advantages over the state-of-the-art approaches and obtains a high control success rate of over 83% for flight parameter control.

CameraRoach: A WiFi- and Camera-Enabled Cyborg Cockroach for Search and Rescue

We describe here our design and implementation of a cyborg insect, called CameraRoach, with onboard camera feedback that can be navigated via remote control providing a first-person view. The camera pack is mounted on the Madagascar hissing cockroach, which is small enough to fit into crevices but also can carry a printed circuit boards with power, communication, and sensor components (visual camera). For navigating the cockroach, we implemented a unique electronic backpack neural stimulator, which allows the cockroach to be maneuvered on a desired path with a joystick. A high-resolution wireless camera, also included in the backpack, sends live images via a WiFi (Wireless Fidelity) network. We present the results of an evaluation experiment with the CameraRoach and compare it with the other state of the art systems like the Beetle-Cam.

Behavioral control and changes in brain activity of honeybee during flapping

INTRODUCTION

Insect cyborg is a kind of novel robot based on insect-machine interface and principles of neurobiology. The key idea is to stimulate live insects by specific stimuli; thus, the flight trajectory of insects could be controlled as anticipated. However, the neuroregulatory mechanism of insect flight has not been elucidated completely at present.

METHODS

To explore the neuro-mechanism of insect flight behaviors, a series of electrical stimulation was applied on the optic lobes of semi-constrained honeybees. Times of flight initiation, flapping frequency, and duration were recorded by a high-speed camera. In addition, flapping and steering initiation experiments of the cyborg honeybee were verified. Moreover, series of local field potential signals of optic lobes during flapping were collected, pre-processed to remove baseline wander and DC components, then analyzed by power spectrum estimation.

RESULTS

A quantitative optimization method and optimal stimulation parameters of flight initiation were presented. Stimulation results showed that the flapping duration differed greatly while the flapping frequency varied with little difference among different individuals. Moreover, there was always a fluctuation peak around 20-30 Hz in power spectral density (PSD) curves during flapping, distinguishing from calm state, which indicated some brain activity changes during flapping.

CONCLUSIONS

Our study presented a range of relatively optimal electrical parameters to initiate honeybee flight behavior. Meanwhile, the regularity of flapping duration and flapping frequency under electrical stimulations with different parameters were given. The feasibility of controlling a honeybee's flight behavior by brain electrical stimulation was verified through the flapping and steering initiation experiment of honeybees under semi-constrained state. PSD fluctuations reflected changes in brain activity during flapping and that those fluctuation characteristics at the specific frequency band could be sensitive determinants to distinguish whether the honeybee was flying or not, which benefits our understanding of honeybee's flapping behavior and furthers the study of honeybee cyborgs.

Intercollicular nucleus electric stimulation encoded “walk forward” commands in pigeons

The bio-robot research field is growing. Robo-pigeons have been successfully programmed to turn left or right; however, a satisfactory method of commanding a robo-pigeon to walk forward is still lacking. This problem has become a roadblock to progress in bio-robot research and applications. In mammals, the midbrain periaqueductal gray region (PAG) plays a key role in mediating defensive reactions in response to fear and anxiety. The avian intercollicular nucleus (ICo) is thought to correspond to the PAG. In this study, we found that microstimulating the ICo could successfully induce a robo-pigeon to walk forward. Compared with stimulation of the previously used archistriatum, the response time was considerably shorter and the behavior accuracy significantly higher. This paper describes in detail the process of controlling a robo-pigeon such that it walks forward and backward along a prescribed straight line. From the results, we draw the conclusion that the ICo is suitable for prompting the “walk forward” order in robo-pigeons.

The robo-pigeon based on the multiple brain regions synchronization implanted microelectrodes

Almost all multichannel microelectrodes are only applied to the same nucleus. The multiple brain regions synchronization implanted microelectrodes can be implanted in the several brain regions at the same time, when used in the robo-animal, which can reduce the operation process, shorten animals operation time. Due to electrode position relatively fixed, errors caused by each separately implanted electrode were reduced and the animal control effect was greatly increased compared to the original electrodes. The electrode fixed time was also extended. This microelectrode provided beneficial reference function for the study of the free state of small animals in different brain regions.

Insect-machine hybrid system

We demonstrated the remote control of insects in free flight via an implantable radio-equipped miniature neural stimulating system. This paper summarizes these results. The pronotum mounted system consisted of neural stimulators, muscular stimulators, a radio transceiver-equipped microcontroller and a microbattery. Flight initiation, cessation and elevation control were accomplished through neural stimulus of the brain which elicited, suppressed or modulated wing oscillation. Turns were triggered through the direct muscular stimulus of either of the basalar muscles. We characterized the response times, success rates, and free-flight trajectories elicited by our neural control systems in remotely-controlled beetles. We believe this type of technology will open the door to in-flight perturbation and recording of insect flight responses.

Insect biofuel cells using trehalose included in insect hemolymph leading to an insect-mountable biofuel cell

In this paper, an insect biofuel cell (BFC) using trehalose included in insect hemolymph was developed. The insect BFC is based on trehalase and glucose oxidase (GOD) reaction systems which oxidize β-glucose obtained by hydrolyzing trehalose. First, we confirmed by LC-MS that a sufficient amount of trehalose was present in the cockroach hemolymph (CHL). The maximum power density obtained using the insect BFC was 6.07 μW/cm(2). The power output was kept more than 10 % for 2.5 h by protecting the electrodes with a dialysis membrane. Furthermore, the maximum power density was increased to 10.5 μW/cm(2) by using an air diffusion cathode. Finally, we succeeded in driving a melody integrated circuit (IC) and a piezo speaker by connecting five insect BFCs in series. The results indicate that the insect BFC is a promising insect-mountable battery to power environmental monitoring micro-tools.