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EungChang Mason Lee,DongUk Seo,JinWoo Jeon,Hyun Myung 제어로봇시스템학회 2021 제어로봇시스템학회 국제학술대회 논문집 Vol.2021 No.10
Exploring an unknown environment with unmanned robots has attracted many interests in the robotics field to replace human resources. Especially, quadruped robots, which can operate in challenging terrains and have high payload capacity, have been widely researched. However, quadruped robots are facing the contact constraints of the legs, namely traversability. In this paper, to explore unknown environments with quadruped robots safely, we propose a novel local exploration planner that utilizes the precomputed trajectories to check traversability and collision at the same time. By strictly checking the collision and traversability in two steps, the admissible path is guaranteed in the receding-horizon manner. In addition, the trajectory considers the kinodynamics and is lightweight thanks to its precomputation. The performance of the proposed method is verified by exploring 3D simulation environments in comparison with one of the state-of-the-art methods.
Comparison of Visual Inertial Odometry using FlightGoggles Simulator for UAV
Eungchang Mason Lee,Inhwan Wee,Taeyeon Kim,David Hyunchul Shim 제어로봇시스템학회 2019 제어로봇시스템학회 국제학술대회 논문집 Vol.2019 No.10
Recently, application of Unmanned Aerial Vehicle (UAV) attract much attention of not only academic but also industrial community. To control and make the most of UAV, state estimation is mandatory and it should work accurately on Real-time on computational-limited onboard PC. Especially, for the cases that GNSS-disabled environments or indoor situation, Visual Inertial Odometry using camera and IMU sensor has been actively studied. Generally, to research and develop the indoor navigation algorithm, high-performanced and super-expensive facilities like motion capture cameras are needed to measure the ground-truth. In this paper, we apply state-of-art Visual Inertial Odometry algorithms for state estimation of UAVs to FlightGoggles simulator which is photorealistic and which reflects UAV’s real dynamics. Moreover, we compare the performance and resource utilization of those algorithms.
Analysis on the performance of VIO according to Trajectory Planning of UAV
EungChang Mason Lee,Hyun Myung 제어로봇시스템학회 2020 제어로봇시스템학회 국제학술대회 논문집 Vol.2020 No.10
Recently, Unmanned Aerial Vehicles (UAVs) have been widely researched to accomplish tasks such as structural inspection, drone racing, and exploration of an unknown environment. To make the most of UAV and correctly estimate its pose with inexpensive and light-weight sensors such as Inertial Measurement Unit (IMU) and cameras, Visual Inertial Odometry (VIO) has been intensively researched. There were a few analyses on the performance of VIO methods where only estimated pose error and utilization of the computing resources were considered. However, the performance of them according to trajectory planning was not treated. Trajectory planning can be one of the main reasons for the drift of localization from VIO since the sensors acquire the data at their sampling rates. In this paper, we analyze the performance of VIO on various trajectories that have different orders of polynomials for the desired position over time and hence different velocity, acceleration, and the first, second derivative of acceleration, using simulator which reflects the real dynamics of UAV. As a result, the higher the order of polynomial for trajectory, the better performance of VIO can be observed.
ChanYoung Kim,EungChang Mason Lee,JunHo Choi,JinWoo Jeon,SeokTae Kim,Hyun Myung 제어로봇시스템학회 2021 제어로봇시스템학회 국제학술대회 논문집 Vol.2021 No.10
Unmanned Aerial Vehicles (UAVs) have been intensively used in various fields thanks to their excellent maneuverability. However, the short operation time of the UAV is limiting the further utilization of the UAV. The limitation of the UAV can be overcome by landing on ground vehicles and charging the battery on them. Therefore, diverse researches have been done on robust landing on ground platforms. Unfortunately, the existing autonomous landing methods have such limitations that a) special tag or marker should be attached on the landing site; b) visibility of the landing site must be secured; c) platform should be static; In this paper, to robustly estimate the relative pose of the moving platform and successfully land on it, we propose a novel robust landing system of the UAV. A neural network based object detection is used to recognize the landing site without a special tag or marker, and an Ultra-wideband (UWB) sensor is adopted to compensate for the limited field of view of the camera. The Extended Kalman Filter (EKF) for estimating the relative position of the moving platform by fusing the information obtained from various sensors is developed. Additionally, a robust autonomous landing controller is also designed. The performance of the proposed method is verified by the simulation of the UAV and the moving platform.