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Scientists have made a silkworm-inspired odour-tracking robot that can locate survivors in disaster areas

Scientists have made a silkworm-inspired odour-tracking robot that can locate survivors in disaster areas

Image: AI Generated

The notion of a robot ‘smelling’ its way through a complex environment has captured the imagination of scientists for years, but has always come with a caveat: what if the robot loses a sensor? In a groundbreaking advance that combines biology and engineering, a new robot, inspired by the humble silkworm, is able to continue its search for smells even after losing a sensor. This not only mirrors the adaptability of nature but also has a number of potential practical applications, from disaster relief work to environmental monitoring. By learning from the adaptability of insects, scientists are shaping the future of robots in a surprisingly practical way.

How the silkworm inspired this odour-tracking robot

The inspiration for this innovation comes from the silkworm moth (Bombyx mori), which is famous for its exceptional ability to sense pheromones.

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Even with a small brain, the moth can locate a partner using the weak scent trails carried by the wind. What is even more surprising is that the moth is still able to navigate even if it loses one of its antennae.According to research published on npj Robotics, “the silkworm moth… can maintain effective navigation using only one antenna.” This biological feature has been used as the basis for developing a robot that does not need to have perfect symmetry in its sensors.

A robot that works even with one sensor

In the traditional method of odour tracking by robots, the robots have to have at least two sensors that are working well to be able to track the odour and move in the direction of the odour. This is because if one of the sensors fails, the performance of the robots is greatly impaired. However, this does not happen with this new method.The method that the robot uses to track the odour is not by the use of algorithms, as seen in the traditional method, but by the use of the behavioural method, which is inspired by insects. The robot does not “panic” if one of the sensors fails, but rather changes its behavioural movements to be able to track the odour with the remaining sensor. From the studies, the performance of the robots is not impaired, as the success rate of the robots remains the same even after the failure of the sensors.This is a significant shift in the way robots are being made, as the traditional method of making robots has been precision-based.

Why odour-tracking robots matter

Odour-based navigation, also called machine olfaction, is an increasingly popular field with numerous practical applications. A robot that is equipped with the capability of detecting and tracing odours could be used for locating survivors in disaster areas, tracing gas leaks, or tracing dangerous substances. According to the researchers from the Research Organisation of Information and Systems (ROIS) involved in this research, “these robots could play pivotal roles in disaster response, hazardous material and explosive detection, and environmental monitoring.” Unlike sniffer dogs, which need training and get tired over time, robots could work without any break and even in dangerous areas without putting anyone’s life in danger.

A step towards smarter robotics

This is because this is the general trend in the field of science, where the focus is on learning from nature to solve complex engineering problems. Insects, although simple, have developed efficient survival mechanisms to live in this world for millions of years. This is being done by replicating the mechanisms which have led to the development of robots that not only have intelligence but also have flexibility.This is best shown by the silkworm-inspired robot, which has shown that losing any of the sensors is not a sign of failure but a sign of adapting differently. This could be the start of something that will revolutionise how robots work in the world, given that this field is constantly evolving. Go to Source

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