• KIPS Transactions on Software and Data Engineering
• /
• v.2 no.5
• /
• pp.353-358
• /
• 2013

In this paper, we present an implementation of indoor flight to navigate to the designated places capable of hands-off autonomous operation within indoor environments. Our flight requires computer vision technique and smartphone device to allow it to be flown indoors without high-performance sensors which are too expensive to commercialization. The experimental result show that proposed implementation is fairly meaningful in a general building.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.37 no.12
• /
• pp.1209-1216
• /
• 2009

This paper presents the pose estimation of a small UAV utilizing visual information from low cost cameras installed indoor. To overcome the limitation of the outside flight experiment, the indoor flight test environment based on multi-camera systems is proposed. Computer vision algorithms for the proposed system include camera calibration, color marker detection, and pose estimation. The well-known extended Kalman filter is used to obtain an accurate position and pose estimation for the small UAV. This paper finishes with several experiment results illustrating the performance and properties of the proposed vision-based indoor flight test environment.

• Journal of the Korean Society of Industry Convergence
• /
• v.23 no.2_2
• /
• pp.255-261
• /
• 2020

We consider the problem of autonomously flying a quadcopter in indoor environments. Navigation in indoor settings poses two major issues. First, real time recognition of the marker captured by the camera. Second, The combination of the distributed images is used to determine the position and orientation of the quadcopter in an indoor environment. We autonomously fly a miniature RC quadcopter in small known environments using an on-board camera as the only sensor. We use an algorithm that combines data-driven image classification with image-combine techniques on the images captured by the camera to achieve real 3D localization and navigation.

• Aerospace Engineering and Technology
• /
• v.13 no.1
• /
• pp.153-165
• /
• 2014

Multi-rotor UAVs are utilized in various fields because of the advantages such that a hovering capability such as helicopters, a simple structure and a relatively high thrust. Recently, AR.Drone manufactured by Parrot is easily operated by beginner due to its internal stabilization loop in the on-board computer and it can be easily applied on various researches for the multi-rotor UAVs by providing an SDK(Software Development Kit). Further this platform can be suitably used for application to swarm flight since it is low cost and relatively small. Therefore, in this paper, we introduce the development process of the controller for indoor swarm flight by using the AR.Drone.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.42 no.9
• /
• pp.752-761
• /
• 2014

With increasing of interest in quad-rotor which has excellent maneuverability recently, a various types of multi-rotor aircraft was developed and commercialized, and there are many kinds of leisure products to be easily operated. In these products, the AR.Drone manufactured by Parrot has an advantage that it is easily operated by user due to the its internal stabilization loop in the on-board computer. Thus it is possible to design the unmanned UAV system easily by using this AR.Drone and its inner loop for the stabilization. For this advantage, KARI(Korea Aerospace Research Institute) has been developing the indoor swarming flight system by using multiple AR.Drones. For this indoor swarming flight, it is necessary that not only the position controller for each AR.Drone, but also the collision avoidance algorithm. Therefore, in this paper, the collision avoidance controller is provided for the swarm flight by using these AR.Drones.

• Aerospace Engineering and Technology
• /
• v.13 no.1
• /
• pp.166-173
• /
• 2014

Recently, small quadcopters have been widely used in various areas ranging from military to entertainment applications because interest in the quadcopter increases. Especially, the research on swarm flight which control quadcopters simultaneously without any collision can increase success probability of a important mission. In addition the swarm flight can be applied for demonstrating choreographed aerial maneuvers such as dancing and playing musical instruments. In this paper, we introduce multiple AR.Drone control system based on motion capture for indoor environment in which quadcopters can recognize current position each other and perform scenario based mission.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.25 no.6
• /
• pp.536-541
• /
• 2015

In this paper, we propose a the image-based automatic flight control system for the mini drone. Automatic flight system with a camera on the ceiling and markers on the floor and landing position is designed in an indoor environment. Images from the ceiling camera is used not only to recognize the makers and landing position but also to track the drone motion. PC sever identifies the location of the drone and sends control commands to the mini drone. Flight controller of the mini drone is designed using state-machine algorithm, PID control and way-point position control method. From the, The proposed automatic flight control system is verified through the experiments of the mini drone. We see that known makers in environment are recognized and the drone can follows the trajectories with the specific ㄱ, ㄷ and ㅁ shapes. Also, experimental results show that the drone can approach and correctly land on the target positions which are set at different height.

• The Journal of Korea Robotics Society
• /
• v.18 no.3
• /
• pp.337-345
• /
• 2023

In this paper, we propose a 3D LiDAR sensor-based costmap generation and path planning algorithm using it for reliable autonomous flight in complex indoor environments. 3D path planning is essential for reliable operation of UAVs. However, existing grid search-based or random sampling-based path planning algorithms in 3D space require a large amount of computation, and UAVs with weight constraints require reliable path planning results in real time. To solve this problem, we propose a method that divides a 3D space into several 2D spaces and a path planning algorithm that considers the distance to obstacles within each space. Among the paths generated in each space, the final path (Best path) that the UAV will follow is determined through the proposed objective function, and for this purpose, we consider the rotation angle of the 2D space, the path length, and the previous best path information. The proposed methods have been verified through autonomous flight of UAVs in real environments, and shows reliable obstacle avoidance performance in various complex environments.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.1738-1741
• /
• 1997

This paper addresses the issue fo target classification and localization with a SONAR for mobiler robot indoor navigation. In particular, multiple refetions of SONAR sound are used actively and interntionally. As for the SONAR sensor, the multiple reflection has been generally considered as one of the noisy phenomena, which is inevitable in the indoor environments. However, these multiple reflections can be a clue for classifying and localizing targets in the indoor environment if those can be controlled and used well. This paper develops a new SONAR sensor module with a reflection plane which can actively create the multiple refection. This paper also intends to suggest a new target classification emthod which uses the multiple refectiions. We approximate the world as being two dimensional and assume that the targets consisting of the indoor environment are pland, corner, and edge. Multiple reflection paths of an acoustic bean by a SONAR are analyzed, by simulations and the patterns of the TOPs (Time Of Flight) and angles of multiple reflections from each target are also analyzed. In addition, a new algorithm for target classification and localization is proposed.

• Aerospace Engineering and Technology
• /
• v.12 no.1
• /
• pp.128-136
• /
• 2013

Recently, the localization recognition system research has been studied using various sensors according to increased interest in autonomous navigation flight. In case of indoor environment which cannot support GPS information, we have to look for another way to recognize current position. The Image-based localization recognition system has been interested although there are lots of way to know current pose. In this paper, we explain the localization recognition system based on mark and implementation of autonomous navigation flight. In order to apply to real environment which cannot support marks, localization based on real-time 3D map building is discussed.