Browsing by Subject "Range sensing"

Now showing 1 - 6 of 6

Open Access
Directional processing of ultrasonic arc maps and its comparison with existing techniques
(Sage Publications Ltd., 2007) Barshan, Billur
A new technique for processing ultrasonic arc maps is proposed and compared to six existing techniques for map-building purposes. These techniques are simple point marking along the line-of-sight, voting and thresholding, morphological processing, Bayesian update scheme for occupancy grids, arc-transversal median algorithm, and triangulation-based fusion. The directional maximum technique, newly proposed in this paper, employs directional processing to extract the map of the environment from ultrasonic arc maps. It aims at overcoming the intrinsic angular uncertainty of ultrasonic sensors in map building, as well as eliminating noise and cross-talk related misreadings. The compared techniques are implemented with a wall-following motion-planning scheme for ground coverage. The comparison is based on experimental data and three complementary error criteria: mean absolute error, correct detection rate for full and empty regions, and computational cost in terms of CPU time. The directional maximum technique offers a very good compromise between mean absolute error and correct detection rate, with a processing time less than one-tenth of a second. Compared to the existing techniques, the directional maximum method is also superior in range accuracy and in eliminating artifacts, resulting in the best overall performance. The results indicate several trade-offs in the choice of ultrasonic arc-map processing techniques.
Open Access
Enhancing 3D range image measurement density via dynamic Papoulis-Gerchberg algorithm
(SAGE Publications, 2018) Kuzucu, E.; Öztürk, D.; Gül, M.; Özbay, B.; Arisoy, A. M.; Sirin, H. O.; Uyanik, I.
As one of the most popular range detection methods, lidar is commonly used in various robotic applications. Although most robotic platforms easily adopt 2D lidar for range sensing, 3D lidar is rarely used in mobile robots, owing to its high cost. Some methods reported in the literature obtain 3D range information by rotating a single 2D lidar device. However, for most of these methods, there is a trade-off between 3D scan frequency and measurement density. Existing methods discussed in the literature for increasing the measurement density in high-frequency lidar have high time complexity and require certain conditions on data distribution. In a previous work, we showed the usability of an image super-resolution method, the Papoulis-Gerchberg (P-G) algorithm, on range data represented in the form of a greyscale image. However, the low convergence rate of the original P-G algorithm impedes its use for online applications. In this study, we advanced the P-G algorithm to drastically reduce the convergence time and improve performance by utilizing previous range images. The proposed algorithm now supports application on a mobile robot with online measurement density enhancement for 3D range images collected by rotating a 2D lidar device around its pitch axis with a high 3D scan frequency. We show illustrative examples for different scenarios to present the effectiveness of the proposed method on a 3D range sensor mounted on a mobile robot.
Open Access
Morphological surface profile extraction with multiple range sensors
(Elsevier, 2001) Barshan, B.; Başkent, D.
A novel method is described for surface pro"le extraction based on morphological processing of multiple range sensor data. The approach taken is extremely #exible and robust, in addition to being simple and straightforward. It can deal with arbitrary numbers and con"gurations of sensors as well as synthetic arrays. The method has the intrinsic ability to suppress spurious readings, crosstalk, and higher-order re#ections, and process multiple re#ections informatively. The performance of the method is investigated by analyzing its dependence on surface structure and distance, sensor beamwidth, and noise on the time-of-#ight measurements. 2001 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
Open Access
Objective error criterion for evaluation of mapping accuracy based on sensor time-of-flight measurements
(2008) Barshan, B.
An objective error criterion is proposed for evaluating the accuracy of maps of unknown environments acquired by making range measurements with different sensing modalities and processing them with different techniques. The criterion can also be used for the assessment of goodness of fit of curves or shapes fitted to map points. A demonstrative example from ultrasonic mapping is given based on experimentally acquired time-of-flight measurements and compared with a very accurate laser map, considered as absolute reference. The results of the proposed criterion are compared with the Hausdorff metric and the median error criterion results. The error criterion is sufficiently general and flexible that it can be applied to discrete point maps acquired with other mapping techniques and sensing modalities as well.
Open Access
Representing and evaluating ultrasonic maps using active snake contours and Kohonen's self-organizing feature maps
(Springer, 2010-05-04) Altun, K.; Barshan, B.
Active snake contours and Kohonen's self-organizing feature maps (SOMs) are employed for representing and evaluating discrete point maps of indoor environments efficiently and compactly. A generic error criterion is developed for comparing two different sets of points based on the Euclidean distance measure. The point sets can be chosen as (i) two different sets of map points acquired with different mapping techniques or different sensing modalities, (ii) two sets of fitted curve points to maps extracted by different mapping techniques or sensing modalities, or (iii) a set of extracted map points and a set of fitted curve points. The error criterion makes it possible to compare the accuracy of maps obtained with different techniques among themselves, as well as with an absolute reference. Guidelines for selecting and optimizing the parameters of active snake contours and SOMs are provided using uniform sampling of the parameter space and particle swarm optimization (PSO A demonstrative example from ultrasonic mapping is given based on experimental data and compared with a very accurate laser map, considered an absolute reference. Both techniques can fill the erroneous gaps in discrete point maps. Snake curve fitting results in more accurate maps than SOMs because it is more robust to outliers. The two methods and the error criterion are sufficiently general that they can also be applied to discrete point maps acquired with other mapping techniques and other sensing modalities.
Open Access
Surface profile determination from multiple sonar data using morphological processing
(1998) Başkent, Deniz
In this thesis, a novel method for surface profile determination using multiple sensors is presented. Our approach is based on morphological processing techniques to fuse the range data from multiple sensor returns in a manner that directly reveals the target surface profile. The method has the intrinsic ability of suppressing spurious readings due to noise, crosstalk, and higher-order reflections, as well as processing multiple reflections informatively. The approach taken is extremely flexible and robust, in addition to being simple and straightforward. It can deal with arbitrary numbers and configurations of sensors as well as synthetic arrays. The profil of any continuous surface with varying curvature can be extracted as long as the curvature of the surface is not too high. The average processing time of the method is of the order of several seconds indicating that the method is viable for real-time applications. The algorithm is verified both by simulations and experiments in the laboratory by processing real sonar data obtained from the Nomad 200 mobile robot. The results are compared to those obtained from a more accurate structured-light system, which is however more complex and expensive.