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

Abstract

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%.

Feedback control of automatic navigation for cyborg cockroach without external motion capture system

“…Longitudinal acceleration ( ) obtained from the IMU sensor was implemented to detect the longitudinal movement of the cockroach. This longitudinal acceleration was noisy and difficult to implement directly to distinguish the cockroach motion between stop and walk [ 1 ]. In this study, a simple parameter ( ) was implemented to activate automatic stimulation to the cerci as expressed in Equation (11) .…”

“…This hybrid cm-scale robot has excellent locomotion and agility in an unknown environment. Cockroaches have been selected as the main platform of hybrid robots due to their size and locomotion [ [1] , [2] , [3] , [4] , [5] , [6] , [7] , [8] , [9] , [10] ]. If overturned, they can self-right on the ground and climb on the obstacle [ 11 ].…”

“…To overcome these issues, researchers have studied how to optimize the cockroach hybrid robot motion by implementing certain algorithms and inertial measuring unit (IMU) sensor. IMU is the most widely used sensor applied to insect hybrid robots to capture the kinematics of the hybrid robots [ 1 , 2 , 4 , 9 , [17] , [18] , [19] , [20] , [21] , [22] , [23] , [24] ]. The previous study implemented predictive feedback control based on the linear and angular velocity obtained from the IMU sensor to the cockroach hybrid robot.…”

“…The study demonstrated that the cyborg cockroach could avoid obstacles/walls and follow them autonomously in the bounded space. The movement of the cockroach could be successfully increased while the stimulation time was reduced to prevent fatigue of the cockroach [ 1 ].

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Automatic Holonomic Mobile Micromanipulator for Submillimeter Objects Inspired by the Rhinoceros Beetle

“…The miniaturization of insect-inspired biorobotic technology holds considerable promise for achieving insect-comparable efficiency, energy conservation, and collaborative operations. [17][18][19][20][21][22][23][24][25][26][27] Mobile manipulation also plays a crucial role in the context of flexible and self-reconfigurable robotic factories. [28][29][30][31] Precision stages have undergone extensive research to enhance positional accuracy.…”