# Wind Source Localization System Based on a Palm-Sized Quadcopter  
[PERSON]  
1 Graduate School of Engineering Science, Osaka University, 1-2 Machikaneyama-cho,  
Toyonaka-shi 560-0043, Japan; [EMAIL_ADDRESS]  
2 Graduate School of Engineering, Kyoto University, Katsura Campus, Nishikyo-ku, Kyoto 615-8540, Japan; [EMAIL_ADDRESS]  
[PERSON]  
2 Graduate School of Engineering, Kyoto University, Katsura Campus, Nishikyo-ku, Kyoto 615-8540, Japan; [EMAIL_ADDRESS]  
[PERSON]  
SLAM (Simultaneous Localization and Mapping) [7], and recently, it has been proposed to utilize a coalition formation game model [8] or multiobjective motion planning strategy [9] to navigate autonomous robots, including UAVs, to a certain waypoint. Moreover, methods that use LiDAR depth information to understand spatial conditions and improve positioning accuracy have been proposed in recent years [10]. These methods are suitable for guiding autonomous robots to general waypoints, but for the problem of locating a particular source (e.g., odor, wind), the utilization of local sensory information can provide efficient navigation in situations where GNSS is not available. This method is represented as a bio-inspired method. Although animals do not have global coordinates such as GNSS, they can achieve efficient navigation by effectively utilizing multiple sensory information that can be acquired from local space. In fact, it has been reported that integrating multiple sensory inputs to determine behavior, as animals do, improves search efficiency in locating an odor source [11; 12; 13]. To employ this bio-inspired method, we need to implement sensors to correctly acquire local information. In the context of rheotaxis or anemotaxis, it is important to correctly implement sensors to detect water streams or air flows. Furthermore, research is being conducted on implementing rheotaxis and anemotaxis in robots [14; 15] to support the chemical source detection, which can be achieved with underwater and ground-running robots. In these studies, sensors that can directly detect water or wind flow are implemented on the robot, and this is achieved using relatively simple control laws. However, anemotaxis has not yet been achieved in a quadcopter. A quadcopter generates a strong airflow in order to fly. This airflow is referred to using the word \"wake\" [16], which has also been used in this paper. To achieve anemotaxis with a quadcopter, distinguishing between the environment wind and the wake and determination of the appropriate direction of movement are crucial. A method has been proposed to measure the wind environment with the quadcopter to estimate wind direction from the relationship between the attitude of the quadcopter as it moves and its attitude that changes due to being blown around by the wind [17; 18]. This method can be used to estimate wind direction using an actual quadcopter. However, a problem remains with the estimation accuracy decreasing in environments where the wind direction changes rapidly. To address this issue, recent studies have reported the successful attachment of a wind sensor to a medium-sized quadcopter for observing natural wind information [19; 20; 21]. This study minimizes the impact of the wake of a quadcopter by positioning the wind sensor at a height away from the central axis of the quadcopter. However, because the primary objective was to observe natural winds, the quadcopter was manually maneuvered to observation locations, measuring environmental winds during hovering without autonomous functionality or anemotactic capability. Consequently, research on the implementation of the anemotaxis ability in the quadcopter is still controversial and underdeveloped. Therefore, this study aims to implement anemotaxis in a quadcopter, enabling autonomous wind source exploration.