The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
A mobile robot that accomplishes high level tasks needs to be able to classify the objects in the environment and to determine their location. In this paper, we address the problem of online object detection in 3D laser range data. The object classes are represented by 3D point-clouds that can be obtained from a set of range scans. Our method relies on the extraction of point features from range images...
This paper describes a LIDAR-based perception system for ground robot mobility, consisting of 3D object detection, classification and tracking. The presented system was demonstrated on-board our autonomous ground vehicle MuCAR-3, enabling it to safely navigate in urban traffic-like scenarios as well as in off-road convoy scenarios. The efficiency of our approach stems from the unique combination of...
This paper presents a feature based 3D mapping approach with regard to obtaining compact models of semi-structured environments such as partially destroyed buildings where mobile robots are to carry out rescue activities. To gather the 3D data, we use a laser scanner, employing a nodding data acquisition system mounted on both real and simulated robots. Our segmentation algorithm comes up from the...
This paper describes a new approach to extract planar features from 3D range data captured by a range imaging sensor-the SwissRanger SR-3000. The focus of this work is to segment vertical and horizontal planes from range images of indoor environments. The method first enhances a range image by using the surface normal information. It then partitions the Normal Enhanced Range Images (NERI) into a number...
The fast reconstruction for 3D environment is a challenging work for autonomous mobile robots. This paper presents an automated 3D scenes reconstruction method based on ICP algorithm. According to the order relations of 3D laser scanning, an effective edge feature extraction method is proposed to extract the edge points in the 3D scenes. The edge points instead of the initial points are used in pairs...
A rigorous investigation on the synergy of mechanical attributes to engineer tactics for measuring human activity in terms of forces, as well as to provide independency and discrimination clarity of action recognition using linear and non-linear classification methodologies from data mining and evolutionary computation, are the main objectives where this paper focuses on. Mechanical analysis is employed...
This paper presents a method for accurately segmenting and classifying 3D range data into particular object classes. Object classification of input images is necessary for applications including robot navigation and automation, in particular with respect to path planning. To achieve robust object classification, we propose the idea of an object feature which represents a distribution of neighboring...
There are many boundaries of artificial objects which are appeared as edges in the image. These line segments as edge impose information for understanding indoor environment. We obtain 3-dimension positional information as we use a stereo camera. There are three dominant vanishing points(VPs) in 3D world. We can separate lines and estimate forward direction by using VP. Groups of such coinciding lines...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.