S&M Young Researcher Paper Award 2020
Recipients: Ding Jiao, Zao Ni, Jiachou Wang, and Xinxin Li [Winner's comments]
Paper: High Fill Factor Array of Piezoelectric Micromachined
Ultrasonic Transducers with Large Quality Factor

S&M Young Researcher Paper Award 2021
Award Criteria
Notice of retraction
Vol. 32, No. 8(2), S&M2292

Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.

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Odor-searching Robot with Insect-behavior-based Olfactory Sensor [PDF]

Junji Horibe, Noriyasu Ando, and Ryohei Kanzaki

(Received March 21, 2021; Accepted September 2, 2021)

Keywords: olfactory sensor, silkmoth, odor searching, machine learning, robot

Extremely sensitive odor sensors are required for odor searching in mobile robots. The male silkmoth (Bombyx mori) is a candidate biosensor because of its high sensitivity to the conspecific sex pheromone with stereotypic searching behavior. Furthermore, the odor preferences of silkmoths can be modified using genetic tools. Therefore, techniques that can easily detect the odor response of silkmoths with high sensitivity have become important for odor detection and searching. In recent years, machine learning has been used to classify the behaviors of silkmoths to estimate the timing of odor reception. Therefore, it is possible to utilize a silkmoth’s behavioral response as an olfactory sensor for robotic odor searching. In this work, we developed an odor- searching mobile robot with an odor sensing device based on a silkmoth’s walking pattern. First, we collected behavioral data with and without odor stimuli. Then, we predicted the presence of an odor using a support vector machine. Finally, we implemented the sensing device in an odor- searching robot and demonstrated that the classifier performance was sufficient for a robot to localize an odor source by utilizing artificial searching algorithms. These results indicated the feasibility of an insect-behavior-based olfactory sensor for robotic odor searching.

Corresponding author: Noriyasu Ando




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