Multisensory-motor integration in olfactory navigation of silkmoth, Bombyx mori, using virtual reality system

Analysis of Odor-Tracking Performance of Silk Moth Using a Sensory-Motor Intervention System

Animals can adaptively behave in different environmental conditions by converting environmental information obtained from their sensory organs into actions. This sensory-motor integration enables the accomplishment of various tasks and is essential for animal survival. This sensory-motor integration also plays an important role in localization to females, relying on sex pheromones floating in space. In this study, we focused on the localization behavior of the adult male silk moth, Bombyx mori. We investigated sensory-motor integration against time delay using odor plume tracking performance as an index when we set a certain time delay for the sensory and motor responses. Given that it is difficult to directly intervene in the sensory and motor functions of the silk moth, we constructed an intervention system based on a mobile behavior measurement system controlled by them. Using this intervention system, not only can timing the detection of the odor in the environment and timing the presentation of the odor to the silk moth be manipulated, but timing the reflection of the movement of the silk moth can also be manipulated. We analyzed the extent to which the localization strategy of the silk moth could tolerate sensory delays by setting a delay to the odor presentation. We also evaluated behavioral compensation by odor sensory feedback by setting a delay to the motor. The results of the localization experiment have shown that the localization success rate did not decrease when there was a motor delay. However, when there was a sensory delay, the success rate decreased depending on the time delay. Analysis of the change in behavior after detection of the odor stimulus has shown that the movement was more linear when we set a motor delay. However, the movement was accompanied by a large rotational movement when there was a delay in the sensory input. This result has suggested that behavior is compensated for the delay in motor function by feedback control of odor sensation, but not when accompanied by sensory delay. To compensate for this, the silk moth may acquire appropriate information from the environment by making large body movements.

Bioinspired Perception and Navigation of Service Robots in Indoor Environments: A Review

Biological principles draw attention to service robotics because of similar concepts when robots operate various tasks. Bioinspired perception is significant for robotic perception, which is inspired by animals' awareness of the environment. This paper reviews the bioinspired perception and navigation of service robots in indoor environments, which are popular applications of civilian robotics. The navigation approaches are classified by perception type, including vision-based, remote sensing, tactile sensor, olfactory, sound-based, inertial, and multimodal navigation. The trend of state-of-art techniques is moving towards multimodal navigation to combine several approaches. The challenges in indoor navigation focus on precise localization and dynamic and complex environments with moving objects and people.

Continuous odor profile monitoring to study olfactory navigation in small animals

Olfactory navigation is observed across species and plays a crucial role in locating resources for survival. In the laboratory, understanding the behavioral strategies and neural circuits underlying odor-taxis requires a detailed understanding of the animal's sensory environment. For small model organisms like Caenorhabditis elegans and larval Drosophila melanogaster, controlling and measuring the odor environment experienced by the animal can be challenging, especially for airborne odors, which are subject to subtle effects from airflow, temperature variation, and from the odor's adhesion, adsorption, or reemission. Here, we present a method to control and measure airborne odor concentration in an arena compatible with an agar substrate. Our method allows continuous controlling and monitoring of the odor profile while imaging animal behavior. We construct stationary chemical landscapes in an odor flow chamber through spatially patterned odorized air. The odor concentration is measured with a spatially distributed array of digital gas sensors. Careful placement of the sensors allows the odor concentration across the arena to be continuously inferred in space and monitored through time. We use this approach to measure the odor concentration that each animal experiences as it undergoes chemotaxis behavior and report chemotaxis strategies for C. elegans and D. melanogaster larvae populations as they navigate spatial odor landscapes.

Determination of trajectories using IKZ/CF inertial navigation: Methodological proposal

Nowadays, there are different methods used in the autonomous navigation task; current solutions include inertial navigation systems (INS). However, these systems present drift errors that are attenuated by the integration of absolute reference systems such as GPS, and antennas, among others. Consequently, few works concentrate efforts on developing a methodology to reduce drift errors in INS due to the widespread practice of incorporating absolute references into their systems. However, absolute references must be placed beforehand, which is not always possible. This work presents an improvement on our methodological proposal IKZ for tracking and localization of moving objects by integrating a complementary filter (CF). The main contribution of this paper is the methodological proposal in the integration between IKZ and CF, maintaining the restrictive properties to the drift error and significantly improving the handling characteristics of the system in real applications. Furthermore, the IKZ/CF was tested with raw data from an MPU-9255 in order to analyze the results between tests.

Robust Moth-Inspired Algorithm for Odor Source Localization Using Multimodal Information

Odor-source localization, by which one finds the source of an odor by detecting the odor itself, is an important ability to possess in order to search for leaking gases, explosives, and disaster survivors. Although many animals possess this ability, research on implementing olfaction in robotics is still developing. We developed a novel algorithm that enables a robot to localize an odor source indoors and outdoors by taking inspiration from the adult male silk moth, which we used as the target organism. We measured the female-localization behavior of the silk moth by using a virtual reality (VR) system to obtain the relationship between multiple sensory stimuli and behavior during the localization behavior. The results showed that there were two types of search active and inactive depending on the direction of odor and wind detection. In an active search, the silk moth moved faster as the odor-detection frequency increased, whereas in the inactive search, they always moved slower under all odor-detection frequencies. This phenomenon was constructed as a robust moth-inspired (RMI) algorithm and implemented on a ground-running robot. Experiments on odor-source localization in three environments with different degrees of environmental complexity showed that the RMI algorithm has the best localization performance among conventional moth-inspired algorithms. Analysis of the trajectories showed that the robot could move smoothly through the odor plume even when the environment became more complex. This indicates that switching and modulating behavior based on the direction of odor and wind detection contributes to the adaptability and robustness of odor-source localization.