Source Localization Robots
Motivation: It is difficult to find the exact odor source position. That's why we learn it!
Material: We use some robots here
Progress: Some of the research findings have already been submitted, published, and presented in international conferences, and journals
This paper proposes a new approach for odor source localization using a low computational controller in the micro quadcopter. Searching for an odor source is an engineering problem, it can be a simple task if a high-computational controller is implemented. However, in reality, a micro quadcopter has a major constraint: the payload limitation where the high-computational controller can be out of the option. In this case, a low computational controller is employed to complement the searching requirement. In this research, the searching algorithm based on bio-inspired behavior of the silkmoth and noise reduction based on the Savitzky-Golay filter is employed. The odor source localization in the micro quadcopter shows a satisfactory result where the test is validated through experimental validation.
Design and Experimental Evaluation of an Odor Sensing Method for a Pocket-Sized Quadcopter [J2]
Animal-in-the-loop system to investigate adaptive behavior [J1]
Description: In this research, we aim to model an adaptive behavior of an animal and implement it in an autonomous robot. The conventional bio-inspired algorithm is difficult to demonstrate the ability as much as the animal because it models without considering the dynamic characteristics of the robot. Therefore, in this study, we constructed an animal-in-the-loop system, which is a novel experimental system for identifying the adaptive behavior of the animal in a form that considers the dynamic characteristics of the robot to be implemented.
(video credits to: https://sshigaki.jimdofree.com/research/)