Digital Library[ Search Result ]
Improvement of XRCE-DDS Communication System for Swarm Environment of Unmanned Vehicles Based on PX4-ROS2
Hyeongyu Lee, Doyoon Kim, Dongoo Lee, Sungtae Moon
http://doi.org/10.5626/JOK.2025.52.3.227
Recently, swarm vehicles are being used in various fields due to the development of swarm operation technology. Among various systems that constitute a swarm vehicle, PX4-ROS2 connects the PX4, an unmanned vehicle control computer, and ROS2 for mission execution through XRCE-DDS (eXtremely Resource Constrained Environments-Data Distribution Service), an open-source-based software that supports real-time communication between devices. However, the operation of swarm unmanned vehicles based on a wireless network using a distributed service of XRCE-DDS is not optimized. It requires communication optimization work for stable operation. In this paper, we analyzed the XRCE-DDS communication structure operating in PX4-ROS2 and proposed a new Discovery mechanism to solve the problem of increased communication volume due to increased nodes during swarm operation. We present a method to enhance the stability and scalability of communication and verified it through simulation.
Prediction of Toothbrushing Position Based on Gyro Sensor Data and its Validation Using Unsupervised Learning-based Clustering
DoYoon Kim, MinWook Kwon, SeungJu Baek, HyeRin Yoon, DaeYeon Lim, Eunah Jo, Seungjae Ryu, Young Wook Kim, Jin Hyun Kim
http://doi.org/10.5626/JOK.2023.50.12.1143
Oral health is an important health indicator that is directly related to longevity. For this reason, oral health has become a key component of public health, from infants to the elderly. The foundation of good oral health is good brushing habits. However, the recommended correct brushing method is not easy to adopt, and this harms oral health. This paper proposes a method to distinguish brushing zones using low-cost IMU sensors to track the correct brushing method. We evaluated the accuracy of the brushing zone estimation method using clustering algorithms in machine learning. In this paper, we propose a method for determining the brushing area based on toothbrush posture alone using the gyro sensor of an IMU sensor. In this paper, we propose a method for determining the brushing area using only the gyro sensor of an IMU sensor based on toothbrush posture. We showed that relatively inexpensive 6-axis IMU gyro sensor data could be used to estimate the user’s brushing area with an accuracy of 80.6%. In addition, we applied a clustering algorithm to these data and trained a logistic regression model using the clustered data to estimate the brushing area. The result was obtained with an accuracy of 86.7%, showing that clustering was effective and that the toothbrush posture-based brushing area estimation proposed in this paper was effective. In conclusion, it is expected that the brushing zone estimation algorithm can be implemented as a function of a relatively low-cost toothbrush and that it can help to maintain oral health by analyzing and improving personal brushing habits.
Outdoor Swarm Flight System Based on the RTK-GPS
SungTae Moon, DoYoon Kim, DonGoo Lee
http://doi.org/10.5626/JOK.2020.47.3.328
The increasing interest in drones has generated new application systems in the various areas. Especially, the drone-show performance applying the swarm flight system impressed many people globally at the Pyeongchang Winter Olympics. However, this technology is Intel technology, not domestic proprietary technology. Thus, the KARI (Korean Aerospace Research Institute) has developed the swarm flight system based on the RTK-GPS and verified the system by showing the 100 drone-show at the independence movement day. In this paper, the propose a robust swarm flight system which can switch the mode according to the RTK-GPS condition. The efficient precise position estimation, communication system, and how to develop the scenario are explained.
Outdoor Swarm Flight System Based on RTK-GPS
SungTae Moon, YeonJu Choi, DoYoon Kim, Myeonghun Seung, HyeonCheol Gong
Recently, the increasing interest in drones has resulted in development of new related technologies. Attention has been focused toward research on swarm flight which controls drones simultaneously without collision. Thus, complicated missions can be completed rapidly through collaboration between drones. Due to low position accuracy, GPS is not appropriate for the outdoor mission involving accurate flight. In addition, the inaccurate position estimation of GPS gives rise to the serious problem of collision, since many drones are controlled in a narrow space. In this study, we increased the accuracy of position estimation through various sensors with Real-Time Kinematic-GPS (RTK-GPS). The mode switching algorithm was proposed to minimize the problem of sensor error. In addition, we introduced the outdoor swarm flight system based on the proposed position estimation.
Search
Journal of KIISE
- ISSN : 2383-630X(Print)
- ISSN : 2383-6296(Electronic)
- KCI Accredited Journal
Editorial Office
- Tel. +82-2-588-9240
- Fax. +82-2-521-1352
- E-mail. chwoo@kiise.or.kr