This paper proposes a study for accurate surface localization system using DWT(Discrete Wavelet Transform) and GPS/INS fusion algorithm. Because the propagation in the underwater is not passed by characteristics of the medium unlike the ground, the sonar system like DVL is used instead of GPS. But since these systems are installed on the seafloor and operated, a long time is required for installation and navigation systems are limited outside of the range area. And it is difficult to estimate position in a three-dimensional considering the depth in actual marine environment. In this paper, before the development of underwater localization system, precisely estimated position system is proposed in a two-dimensional by developing surface localization system using removing noise and disturbance with DWT and relatively inexpensive GPS and INS sensor.
We present a robust power transmission lines detection method based on vanishing point estimation. Vanishing point estimation can be helpful to detect power transmission lines because
parallel lines converge on the vanishing point in a projected 2D image. However, it is not easy to estimate the vanishing point correctly in an image with complex background. Thus, we first propose a vanishing point estimation method on power transmission lines by using a probabilistic voting procedure based on intersection points of line segments. In images obtained by our system, power transmission lines are located in a fan-shaped area centered on this estimated vanishing point, and therefore we select the line segments that converge to the estimated vanishing point as candidate line segments for power transmission lines only in this fan-shaped area. Finally, we detect the power transmission lines from these candidate line segments. Experimental results show that the proposed method is robust to noise and efficient to detect power transmission lines.
This paper presents a method of improving the pose recognition accuracy of objects by using Kinect sensor. First, by using the SURF algorithm, which is one of the most widely used local features point algorithms, we modify inner parameters of the algorithm for efficient object recognition. The proposed method is adjusting the distance between the box filter, modifying Hessian matrix, and eliminating improper key points. In the second, the object orientation is estimated based on the homography. Finally the novel approach of Auto-scaling method is proposed to improve accuracy of object pose estimation. The proposed algorithm is experimentally tested with objects in the plane and its effectiveness is validated.
This paper introduces a graphical user interface design that is aimed to apply to the surveillance and security robot, which is the pilot program for the army unmanned light combat vehicle. It is essential to consider the activities of robot users under the changing security environment in order to design the efficient graphical user interface between user and robot to accomplish the designated mission. The proposed design approach firstly identifies the user activities to accomplish the mission in the standardized scenarios of military surveillance and security operation and then develops the hierarchy of the interface elements that are required to execute the tasks in the surveillance and security scenarios. The developed graphical user interface includes input control component, navigation component, information display component, and accordion and verified by the potential users from the various skilled levels with the military background. The assessment said that the newly developed user interface includes all the critical elements to execute the mission and is simpler and more intuitive compared to the legacy interface design that was more focused on the technical and functional information and informative to the system developing engineers rather than field users.
Recent developments in robotics and intelligent vehicle area, bring interests of people in an autonomous driving ability and advanced driving assistance system. Especially fully automatic parking ability is one of the key issues of intelligent vehicles, and accurate parked vehicles detection is essential for this issue. In previous researches, many types of sensors are used for detecting vehicles, 2D LiDAR is popular since it offers accurate range information without preprocessing. The L shape feature is most popular 2D feature for vehicle detection, however it has an ambiguity on different objects such as building, bushes and this occurs misdetection problem. Therefore we propose the accurate vehicle detection method by using a 3D complete vehicle model in 3D point clouds acquired from front inclined 2D LiDAR. The proposed method is decomposed into two steps: vehicle candidate extraction, vehicle detection. By combination of L shape feature and point clouds segmentation, we extract the objects which are highly related to vehicles and apply 3D model to detect vehicles accurately. The method guarantees high detection performance and gives plentiful information for autonomous parking. To evaluate the method, we use various parking situation in complex urban scene data. xperimental results shows the qualitative and quantitative performance efficiently.
Peg-in-hole assembly is the most representative task for a robot to perform under contact conditions. Various strategies for accomplishing the peg-in-hole task with a robot exist, but the existing strategies are not sufficiently practical to be used for various assembly tasks in a human environment because they require additional sensors or exclusive tools. In this paper, the peg-in-hole assembly experiment is performed with anthropomorphic hand arm robot without extra sensors or devices using “intuitive peg-in-hole strategy”. From this work, the probability of applying the peg-in-hole strategy to a common assembly task is verified.