Ladar System Identifies Obstacles Partly Hidden by Grass

A ladar-based system now undergoing development is intended to enable an autonomous mobile robot in an outdoor environment to avoid moving toward trees, large rocks, and other obstacles that are partly hidden by tall grass. The design of the system incorporates the assumption that the robot is capable of moving through grass and provides for discrimination between grass and obstacles on the basis of geometric properties extracted from ladar readings as described below. The system (see figure) includes a ladar system that projects a range-measuring pulsed laser beam that has a small angular width of radians and is capable of measuring distances of reflective objects from a minimum of dmin to a maximum of dmax. The system is equipped with a rotating mirror that scans the beam through a relatively wide angular range of in a horizontal plane at a suitable small height above the ground. Successive scans are performed at time intervals of seconds. During each scan, the laser beam is fired at relatively small angular intervals of radians to make range measurements, so that the total number of range measurements acquired in a scan is Ne = /

Improving the mobility performance of autonomous unmanned ground vehicles by adding the ability to 'Sense/Feel' their local environment.

This paper follows on from earlier work detailed in output one and critically reviews the sensor technologies used in autonomous vehicles, including robots, to ascertain the physical properties of the environment including terrain sensing. The paper reports on a comprehensive study done in terrain types and how these could be determined and the appropriate sensor technologies that can be used. It also reports on work currently in progress in applying these sensor technologies and gives details of a prototype system built at Middlesex University on a reconfigurable mobility system, demonstrating the success of the proposed strategies. This full paper was subject to a blind refereed review process and presented at the 12th HCI International 2007, Beijing, China, incorporating 8 other international thematic conferences. The conference involved over 250 parallel sessions and was attended by 2000 delegates. The conference proceedings are published by Springer in a 17 volume paperback book edition in the Lecture Notes in Computer Science series (LNCS). These are available on-line through the LNCS Digital Library, readily accessible by all subscribing libraries around the world, published in the proceedings of the Second International Conference on Virtual Reality, ICVR 2007, held as Part of HCI International 2007, Beijing, China, July 22-27, 2007. It is also published as a collection of 81 papers in Lecture Notes in Computer Science Series by Springer

Finding Organized Structures in 3-D Ladar Data

In this paper, we address the problem of finding organized thin structures in three-dimensional (3-D) data. Linear and planar structures segmentation received much attention but thin structures organized in complex patterns remain a challenge for segmentation algorithms. We are interested especially in the problems posed by repetitive and symmetric structures acquired with a laser range finder. The method relies on 3-D data projections along specific directions and 2-D histograms comparison. The sensitivity of the classification algorithm to the parameter settings is evaluated and a segmentation method proposed. We illustrate our approach with data from a concertina wire in terrain with vegetation

Spectral LADAR: Active Range-Resolved Imaging Spectroscopy

Imaging spectroscopy using ambient or thermally generated optical sources is a well developed technique for capturing two dimensional images with high per-pixel spectral resolution. The per-pixel spectral data is often a sufficient sampling of a material's backscatter spectrum to infer chemical properties of the constituent material to aid in substance identification. Separately, conventional LADAR sensors use quasi-monochromatic laser radiation to create three dimensional images of objects at high angular resolution, compared to RADAR. Advances in dispersion engineered photonic crystal fibers in recent years have made high spectral radiance optical supercontinuum sources practical, enabling this study of Spectral LADAR, a continuous polychromatic spectrum augmentation of conventional LADAR. This imaging concept, which combines multi-spectral and 3D sensing at a physical level, is demonstrated with 25 independent and parallel LADAR channels and generates point cloud images with three spatial dimensions and one spectral dimension. The independence of spectral bands is a key characteristic of Spectral LADAR. Each spectral band maintains a separate time waveform record, from which target parameters are estimated. Accordingly, the spectrum computed for each backscatter reflection is independently and unambiguously range unmixed from multiple target reflections that may arise from transmission of a single panchromatic pulse. This dissertation presents the theoretical background of Spectral LADAR, a shortwave infrared laboratory demonstrator system constructed as a proof-of-concept prototype, and the experimental results obtained by the prototype when imaging scenes at stand off ranges of 45 meters. The resultant point cloud voxels are spectrally classified into a number of material categories which enhances object and feature recognition. Experimental results demonstrate the physical level combination of active backscatter spectroscopy and range resolved sensing to produce images with a level of complexity, detail, and accuracy that is not obtainable with data-level registration and fusion of conventional imaging spectroscopy and LADAR. The capabilities of Spectral LADAR are expected to be useful in a range of applications, such as biomedical imaging and agriculture, but particularly when applied as a sensor in unmanned ground vehicle navigation. Applications to autonomous mobile robotics are the principal motivators of this study, and are specifically addressed

Nonlinear Time-Variant Response in an Avalanche Photodiode Array Based Laser Detection and Ranging System

This research effort identifies and models the nonlinear time-variant behavior exhibited by an avalanche photodiode (APD) array based Laser Ranging and Detection (LADAR) system. Based on the original Linear Time-Invariant (LTI) model, the evolution of error in the LADAR signal is examined sequentially from the outgoing pulse through signal digitization. This error evolution shows that the LTI model does not contain a mechanism for causing the observed signal deviations or the failure to meet the Cramer-Rao lower bound for range accuracy. A nonlinear time-variant model is developed based on the interactions of the avalanche photodiodes in the array with the array\u27s voltage regulator. In the refined model, the sum photo-current for the entire array loads the voltage regulator. The resulting reverse bias voltage variations cause the responsivity of each APD to vary in a nonlinear fashion. Because each APD in the array\u27s responsivity depends upon the entire array\u27s photonic loading, each individual APD\u27s response is time variant

A Nonparametric Approach to Segmentation of Ladar Images

The advent of advanced laser radar (ladar) systems that record full-waveform signal data has inspired numerous inquisitions which aspire to extract additional, previously unavailable, information about the illuminated scene from the collected data. The quality of the information, however, is often related to the limitations of the ladar camera used to collect the data. This research project uses full-waveform analysis of ladar signals, and basic principles of optics, to propose a new formulation for an accepted signal model. A new waveform model taking into account backscatter reflectance is the key to overcoming specific deficiencies of the ladar camera at hand, namely the ability to discern pulse-spreading effects of elongated targets. A concert of non-parametric statistics and familiar image processing methods are used to calculate the orientation angle of the illuminated objects, and the deficiency of the hardware is circumvented. Segmentation of the various ladar images performed as part of the angle estimation, and this is shown to be a new and effective strategy for analyzing the output of the AFIT ladar camera