Investigating cyborg cockroach movement optimization with machine learning

Machine Learning

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Scientists at Osaka University designed a cyborg cockroach and optimized its movement using machine learning-based auto-stimulation. credit: Cyborgs and bionic systems

Have you ever wondered why some insects, like cockroaches, prefer to stay in the dark, or to reduce movement? Some might say it’s a habit of being. Another question is whether it is possible to correct this habit of cockroaches, moving in the dark as they move in bright backgrounds.

Scientists at Osaka University may have answered this question by transforming cockroaches into cyborgs.they published the study in the journal Cyborgs and bionic systems.

Over millions of years of evolution, animals in nature have a remarkable ability to survive and thrive in hostile environments. In recent years, these animals have inspired roboticists to develop automatic machines that recreate some of these vanished abilities—biologically inspired biomimetic robots.

An alternative to this method is to implant stimulation electrodes into the brain or peripheral nervous system to control movement and build controllable machines directly into natural animals called cyborgs. Among these studies, cyborg insects have received increasing attention due to their availability, simpler neuromuscular pathways, and easier manipulation to invasively stimulate the peripheral nervous system or muscles. increase.

Cockroaches have incredible locomotion capabilities, vastly outperforming biomimetic robots of similar size. With such agile locomotion, the cyborg he cockroach is therefore well suited for search and rescue missions in unknown and unstructured environments that are largely inaccessible to conventional robots.

“Cockroaches prefer to stay in dark, confined spaces rather than bright, open spaces. In addition, they tend to be more active in hotter environments,” said study author, a robotics engineer at Osaka University’s Department of Mechanical Engineering. One Keisuke Morishima explains. Natural behavior hinders exploitation of cockroaches for search and rescue applications in environments under unknown rubble. Mini live stream cameras mounted on cockroaches in areas with low or no light for real-time surveillance purposes is difficult to apply.”

“This study aims to optimize the locomotion performance of cyborg cockroaches,” said Morishima. To this end, they proposed a machine learning-based approach to automatically detect the locomotion state of this cyborg his cockroach via his IMU measurements. When cockroaches stop or freeze in the dark or cool environment, electrical stimulation is applied to their brains to move them.

“In this online detector, the stimulus is kept to a minimum to prevent cockroaches from becoming fatigued by overstimulation,” said Morishima’s colleague Mokamad Aryanto of the Department of Mechanical Engineering at Osaka University.

This idea of ​​limiting electrical stimulation to necessary situations, determined by AI algorithms via on-board measurements, is intuitively promising. “You don’t have to control a cyborg like you control a robot. Cyborgs can have some degree of autonomy, which is the basis for agile locomotion. You just have to rotate it, and it will change direction if you’re walking the wrong way, or move if it suddenly stops,” Morishima said.

“Cyborgs equipped with such a system were able to increase the average search rate by 68%, the distance traveled by 70%, and stop time by 78%,” the study authors said. . “We have shown that it is possible to apply electrical stimulation to the neck of cockroaches. Cockroaches are able to overcome their natural habits, for example, in the dark and cold where they normally move slower. It can increase movement in the environment.”

“In this study, cerci were stimulated to induce free locomotion in the Madagascar hissing cockroach (MHC).”

For more information:
Mochammad Ariyanto et al., Optimizing Movement of Cyborg Cockroaches in Bounded Space Incorporating Machine Learning, Cyborgs and bionic systems (2023). DOI: 10.34133/cbsystems.0012

Provided by Beijing Institute of Technology Press Co., Ltd.

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