Cyborg Insects Research Articles

Cyborg insect repeatable self-righting locomotion assistance using bio-inspired 3D printed artificial limb

Cyborg insects have emerged as a promising solution for rescue missions, owing to their distinctive and advantageous mobility characteristics. These insects are outfitted with electronic backpacks affixed to their anatomical structures, which endow them with imperative communication, sensing, and control capabilities essential for effecting survivor retrieval. Nevertheless, the attachment of supplementary loads to the insect’s body can exert adverse effects on their intrinsic self-righting locomotion when confronted with fall or shock scenarios. To address this challenge, the present study introduces a bio-inspired 3D-printed artificial limb that serves to facilitate the maneuverability of cyborg insects amidst unpredictable conditions. Drawing inspiration from the natural self-righting motion exhibited by Coccinellidae, we have successfully identified a solution that can be transferred to the electronic backpack utilized by G. portentosa. Incorporation of the bio-inspired artificial wing-like limb has notably enabled the cyborg insect to achieve a remarkable tilting angle of 112°, thereby significantly amplifying the success ratio of self-righting under conditions closely emulating those prevalent in disaster areas. Moreover, we have replicated the expansion and contraction kinematics to ensure seamless motion progression within confined spaces. Importantly, the fabricated device proffered in this study has been meticulously designed for facile reproducibility employing commonly available tools, thereby serving as an inspirational catalyst for fellow researchers engaged in the advancement of 3D-printed limb development aimed at expanding the functional capacities of cyborg insects.

Locomotion Control of Cyborg Insects by Charge-Balanced Biphasic Electrical Stimulation.

The integration of electronic stimulation devices with insects in the context of cyborg insect systems has great application potential, particularly in the fields of environmental monitoring, urban surveillance, and rescue missions. Despite considerable advantages compared to the current robot technology, including flexibility, durability, and low energy consumption, this integration faces certain challenges related to the potential risk of charge accumulation caused by prolonged and repetitive electrical stimulations. To address these challenges, this study proposes a universal system for remote signal output control using infrared signals. The proposed system integrates high-precision digital-to-analog converters capable of generating customized waveform electrical stimulation signals within defined ranges. This enhances the accuracy of locomotion control in cyborg insects while maintaining real-time control and dynamic parameter adjustment. The proposed system is verified by experiments. The experimental results show that the signals generated by the proposed system have a success rate of over 76.25% in controlling the turning locomotion of cyborg insects, which is higher than previously reported results. In addition, the charge-balanced characteristics of these signals can minimize muscle tissue damage, thus substantially enhancing control repeatability. This study provides a comprehensive solution for the remote control and monitoring of cyborg insects, whose flexibility and adaptability can meet various application and experimental requirements. The results presented in this study lay a robust foundation for further advancement of various technologies, particularly those related to cyborg insect locomotion control systems and wireless control mechanisms for cyborg insects.

A newly developed chemical locomotory booster for cyborg insect to sustain its activity and to enhance covering performance

Terrestrial insect-machine hybrid robots have long been discussed as alternatives to artificial centimetre-scale mobile robots. These hybrid robots can possess various functionalities (e.g., localization, object detection) by embedding electronic devices while also benefitting from the insects' robust mobility. However, as insects have relatively low walking speed and insensitivity after repeated electrical stimulation, their motion activeness is hard to maintain at a high level. This study attempts to exploit chemical stimulation to boost the insects' walking activity. The use of methyl salicylate as a chemical booster was examined for improving walking activity. The chemical increased the insects' walking speed by 24.3%, which in turn extended their travel distance and region coverage. Also, methyl salicylate still retained the insects' reaction to the electrical induction. By incorporating the locomotory improvements of methyl salicylate with an electrical stimulation protocol, the hybrid robots could reach a terrain coverage speed of 21.6 cm2/s, much higher than only implementing the electrical stimulation (6.8 cm2/s) or no external stimulation at all (1.2 cm2/s). Overall, this is the first demonstration of methyl salicylate's boosting effect on the insects' activity and improving terrain coverage, filling a crucial gap in practical uses of terrestrial insect-machine hybrid robots.

Resilient conductive membrane synthesized by in-situ polymerisation for wearable non-invasive electronics on moving appendages of cyborg insect

By leveraging their high mobility and small size, insects have been combined with microcontrollers to build up cyborg insects for various practical applications. Unfortunately, all current cyborg insects rely on implanted electrodes to control their movement, which causes irreversible damage to their organs and muscles. Here, we develop a non-invasive method for cyborg insects to address above issues, using a conformal electrode with an in-situ polymerized ion-conducting layer and an electron-conducting layer. The neural and locomotion responses to the electrical inductions verify the efficient communication between insects and controllers by the non-invasive method. The precise “S” line following of the cyborg insect further demonstrates its potential in practical navigation. The conformal non-invasive electrodes keep the intactness of the insects while controlling their motion. With the antennae, important olfactory organs of insects preserved, the cyborg insect, in the future, may be endowed with abilities to detect the surrounding environment.

Cyborg insects: From free-state control to autonomous intelligent regulation

Cyborg insects: From free-state control to autonomous intelligent regulation

Intelligent Insect–Computer Hybrid Robot: Installing Innate Obstacle Negotiation and Onboard Human Detection onto Cyborg Insect

Developing small mobile robots for Urban Search and Rescue (USAR) is a major challenge due to constraints in size and power required to perform vital functions such as obstacle navigation, victim detection, and wireless communication. Drawing upon the idea that insects’ locomotion can be controlled, what if we further utilize the insects’ intrinsic ability to avoid obstacles? Herein, a cockroach hybrid robot (≈ 1.5 cm height, 5.7 cm length) that implements the abovementioned functions is developed. It is tested in an arena with randomly placed obstacles, and a motion capture system is used to track the insect's position among the untracked obstacles. A navigation algorithm that uses an inertial measurement unit (IMU) is developed to heuristically predict the insect's situation and stimulate the insect to escape nearby obstacles. The utilization of insect's intrinsic locomotor ability and low‐powered IMU reduces the onboard power load, allowing the addition of a human‐detecting function. An image classification model enables the use of an onboard low‐resolution infrared camera for human detection. Consequently, a single hybrid robot is established that includes locomotion control, autonomous navigation in obstructed areas, onboard human detection, and wireless communication, representing a significant step toward real USAR application.

Movement Optimization for a Cyborg Cockroach in a Bounded Space Incorporating Machine Learning

Cockroaches can traverse unknown obstacle-terrain, self-right on the ground and climb above the obstacle. However, they have limited motion, such as less activity in light/bright areas and lower temperatures. Therefore, the movement of the cyborg cockroaches needs to be optimized for the utilization of the cockroach as a cyborg insect. This study aims to increase the search rate and distance traveled by cockroaches and reduce the stop time by utilizing automatic stimulation from machine learning. Multiple machine learning classifiers were applied to classify the offline binary classification of the cockroach movement based on the inertial measuring unit input signals. Ten time-domain features were chosen and applied as the classifier inputs. The highest performance of the classifiers was implemented for the online motion recognition and automatic stimulation provided to the cerci to trigger the free walking motion of the cockroach. A user interface was developed to run multiple computational processes simultaneously in real time such as computer vision, data acquisition, feature extraction, automatic stimulation, and machine learning using a multithreading algorithm. On the basis of the experiment results, we successfully demonstrated that the movement performance of cockroaches was importantly improved by applying machine learning classification and automatic stimulation. This system increased the search rate and traveled distance by 68% and 70%, respectively, while the stop time was reduced by 78%.

Integration of body-mounted ultrasoft organic solar cell on cyborg insects with intact mobility

Cyborg insects have been proposed for applications such as urban search and rescue. Body-mounted energy-harvesting devices are critical for expanding the range of activity and functionality of cyborg insects. However, their power outputs are limited to less than 1 mW, which is considerably lower than those required for wireless locomotion control. The area and load of the energy harvesting device considerably impair the mobility of tiny robots. Here, we describe the integration of an ultrasoft organic solar cell module on cyborg insects that preserves their motion abilities. Our quantified system design strategy, developed using a combination of ultrathin film electronics and an adhesive–nonadhesive interleaving structure to perform basic insect motion, successfully achieved the fundamental locomotion of traversing and self-righting. The body-mounted ultrathin organic solar cell module achieves a power output of 17.2 mW. We demonstrate its feasibility by displaying the recharging wireless locomotion control of cyborg insects.

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.

Experimental Evaluation of Teleoperated Control of Cyborg Insects between Bangladesh and Japan

The teleoperation system is very popular for various medical, industrial, and automation applications. During the covid19 pandemic, people understood the importance of the teleoperation system because people could not move from one place to another for travel restrictions. Recently cyborg insects have been a hot research topic for search and rescue operations. However, controlling cyborg insects is not easy because insects are living things and have a biological control system. Only experts can balance the biological and electrical control systems. Otherwise, too much stimulation could kill the insects. This study aimed to develop a cyborg cockroach controlling system for search and rescue operations using the teleoperation technique. The teleoperation system communication link was established between Japan to Bangladesh. These experimental results show that the cyborg insects control accuracy 88% using a teleoperation system. Finally, this study will help control the cyborg insects for search and rescue operations by an expert operator anywhere any the world.

Cyborg Insects: Bug or a Feature?

Cyborg insects are a major part of the vision of future interactions of the living world and technology, including but not limited to the Internet of Living Things (IoLT). They are crawling or flying insects with additional electronic circuitry allowing remote control of their movement and collection of sensory data. In this critical review, we survey the historical development of cyborg insects engineering, from the first backpacks on insects used for communication and sensing, to different methods of control and actuation of insects’ locomotion. We review the suggested applications of cyborg insects ranging from military use to agriculture, pointing out the problematic connotations of swarms and cyborgs in these contexts. We address the applications and the narratives around engineered insects from the perspective of philosophy, economy, law, and politics. We add perspectives on emancipatory potential of cyborg technology and where the future of it could lie.

Experimental Verification on Steering Flight of Honeybee by Electrical Stimulation

The artificial locomotion control strategy is the fundamental technique to ensure the accomplishment of the preset assignments for cyborg insects. The existing research has recognized that the electrical stimulation applied to the optic lobes was an appropriate flight control strategy for small insects represented by honeybee. This control technique has been confirmed to be effective for honeybee flight initiation and cessation. However, its regulation effect on steering locomotion has not been fully verified. Here, we investigated the steering control effect of honeybee by applying electrical stimulation signals with different duty cycles and frequencies on the unilateral optic lobes and screened the stimulus parameters with the highest response successful rate. Moreover, we confirmed the effectiveness of steering control by verifying the presence of rotation torque on tethered honeybees and the body orientation change of crawling honeybees. Our study will contribute some reliable parameter references to the motion control of cyborg honeybees.

A Cyborg Insect Reveals a Function of a Muscle in Free Flight

While engineers put lots of effort, resources, and time in building insect scale micro aerial vehicles (MAVs) that fly like insects, insects themselves are the real masters of flight. What if we would use living insect as platform for MAV instead? Here, we reported a flight control via electrical stimulation of a flight muscle of an insect-computer hybrid robot, which is the interface of a mountable wireless backpack controller and a living beetle. The beetle uses indirect flight muscles to drive wing flapping and three major direct flight muscles (basalar, subalar, and third axilliary (3Ax) muscles) to control the kinematics of the wings for flight maneuver. While turning control was already achieved by stimulating basalar and 3Ax muscles, electrical stimulation of subalar muscles resulted in braking and elevation control in flight. We also demonstrated around 20 degrees of contralateral yaw and roll by stimulating individual subalar muscle. Stimulating both subalar muscles lead to an increase of 20 degrees in pitch and decelerate the flight by 1.5 m/s2 as well as an induce in elevation of 2 m/s2.

Control Method of Cyborg Insect inspired by Biological Behaviors

This paper propose real time control method of cyborg insect inspired by biological behaviors. In experiments, we successfully demonstrated navigating an individual insect using IMU data based on machine learning analysis with minimum electrical stimulation.

Sideways Walking Control of a Cyborg Beetle

Cyborg insect also referred as insect-machine hybrid robot, consists of a living insect platform and an electronic backpack mounted on. The small size and magnificent walking ability of the insect make this hybrid system a potential candidate for search and rescue missions. The great locomotory capability helps the insect to cope with the complex and unpredictable terrains, whereas the tiny dimension allows it to easily enter the debris of post-disaster sites. There is a necessity to establish more controllable mobility for cyborg insects to develop more efficient maneuver plans. Here, this study demonstrates the control of sideways and forward walking in a cyborg beetle by emulating the touch responses of mechanoreceptors on the insect's elytra using the electrical stimulation. The beetle walked sideways leftward when the right elytron was stimulated, and vice versa. The forward control was attained by stimulating both elytra simultaneously. In addition, these elicited motions were found to be graded by tuning the stimulation frequency as increasing the frequency sped up the sideways walking and slowed down the forward velocity. Besides complementing the controllability of the cutting-edge cyborg insects, this graded response is essential for improving the navigation in cyborg insects for search and rescue missions.

An HSR Data Model for Cyborg Insect Research Experiments

Research on cyborg intelligent insects requires the experiment platform to collect data from the distributed sensing models and process the multi-modal signals in real-time. To overcome these issues, we present a novel data model, naming as the Hybrid-synchronizedrealtime (HSR) data model, which can synchronize the hybrid raw data channels by a meta data integration method and process them with a fixed priority scheduling algorithm. Real animal experiments show that the insect-machine experiment platform based on the HSR data model can fully satisfy the requirements of cyborg intelligent insect research, especially in dealing with the technical challenges of data synchronization, real-time processing and hybrid data integration. It provides an efficient approach to implement the experiment platform and thus aid the frontier research on cyborg insects.

Abdominal-Waving Control of Tethered Bumblebees Based on Sarsa With Transformed Reward.

Cyborg insects have attracted great attention as the flight performance they have is incomparable by micro aerial vehicles and play a critical role in supporting extensive applications. Approaches to construct cyborg insects consist of two major issues: 1) the stimulating paradigm and 2) the control policy. At present, most cyborg insects are constructed based on invasive methods, requiring the implantation of electrodes into neural or muscle systems, which would harm the insects. As the control policy is basically manual control, the shortcomings of which lie in the requirement of excessive amount of experiments and focused attention. This paper presents the design and implementation of a noninvasive and much safer cyborg insect system based on visual stimulation. The tethered paradigm is adopted here and we look at controlling the flight behavior of bumblebees, especially the abdominal-waving behavior, in the context of a model-free reinforcement learning problem. The problem is formulated as a finite and deterministic Markov decision process, where the agent is designed to change the abdominal-waving behavior from the initial state to the target state. Sarsa with transformed reward function which can speed up the learning process is employed to learn the optimal control policy. Learned policies are compared to the stochastic one by evaluating the results of ten bumblebees, demonstrating that abdominal-waving state can be modulated to approximate the target state quickly with small deviation.

Geometric Learning and Topological Inference With Biobotic Networks

In this study, we present and analyze a framework for geometric and topological estimation for mapping of unknown environments. We consider agents mimicking motion behaviors of cyborg insects, known as biobots , and exploit coordinate-free local interactions among them to infer geometric and topological information about the environment, under minimal sensing and localization constraints. A metric estimation procedure is presented over a graphical representation referred to as the encounter graph in order to construct a geometric point cloud using manifold learning techniques. Topological data analysis (TDA) along with the proposed classification method is used to infer robust topological features of the space (e.g., existence of obstacles). We examine the asymptotic behavior of the proposed metric in terms of the convergence to the geodesic distances in the underlying manifold of the domain, and provide stability analysis results for the topological persistence. The proposed framework and its convergences and stability analysis are demonstrated through numerical simulations and experiments with Hexbugs.

A framework for mapping with biobotic insect networks: From local to global maps

We present an approach for global exploration and mapping of unknown environments using a swarm of cyborg insects, known as biobots, for emergency response scenarios under minimal sensing and localization constraints. We exploit natural stochastic motion models and controlled locomotion of biobots in conjunction with an aerial leader to explore and map a domain of interest. A sliding window strategy is adopted to construct local maps from coordinate free encounter information of the agents by means of local metric estimation. Robust topological features from these local representations are extracted using topological data analysis and a classification scheme. These maps are then merged into a global map which can be visualized using a graphical representation, that integrates geometric as well as topological features of the environment. Simulation and experimental results with biologically inspired robotic platform are presented to illustrate and verify the correctness of our approach, which provides building blocks for SLAM with biobotic insects.