In this study, we developed a novel unfixed-type experimental system that we call a '3-DOF servosphere.' This system comprises one sphere and three omniwheels that support the sphere. The measurement method is very simple. An experimental animal is placed on top of the sphere. The position and heading angle of the animal are observed by using a high-speed camera installed above the sphere. Because the system can rotate the sphere with three degrees of freedom (DOFs) independently, the position and heading angle at the origin can be maintained without fixing the body. This system can be used to measure an animal's natural behavior while simultaneously providing it with precise stimuli. Moreover, electrodes can be inserted at specific sites to measure biosignals with locomotion. Therefore, this system can simultaneously measure the stimulus input-internal state-locomotion output of an animal. In this study, we focused on the chemical plume tracing (CPT) behavior of the Bombyx mori male silkworm moth in order to identify its CPT algorithm for mounting on a robot. In an experiment, we simultaneously measured the stimulus input, flight muscle electromyogram (EMG), and CPT behavior by using the 3-DOF servosphere to verify the system. We elucidated the relationship between the CPT behavior and flight muscle EMG.
In this study, we developed a behavior measurement system named 3D servo-sphere. The system is composed of one sphere and three omni-wheels that support the sphere. A male silkworm moth, Bombyx mori, is put on the top of the sphere. The position and the body angle of a moth are observed by a high-speed camera that is installed above a moth. Since the system can rotate the sphere in 3-DOF independently, we can keep the position and the body angle at the origin without any body-fixture. By the proposed system, we can observe natural behavior of a moth during CPT (Chemical Plume Tracing). The system also enables that we can give stimulus precisely without fixing the animal, because the feedback system keeps the position of the head of a moth. By using this, we can observe the relationship between input stimulus and output action in long run. By connecting to a virtual space in a computer, we can apply modeled environment to a real moth. The system will be effective to identify transfer functions from stimulus to behavior. 1.
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