Status report on next-generation LADAR for driving unmanned ground vehicles

Juberts, Maris; Barbera, Anthony J.

doi:10.1117/12.580235

Cited by 14 publications

(7 citation statements)

References 7 publications

(3 reference statements)

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“…To estimate the rotation matrix, a minimum of two non-parallel planar surfaces is required. It can be shown that equation (10) results in the least squares estimate of R.…”

Section: Attitude Change Estimationmentioning

confidence: 98%

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Use of 3D laser radar for navigation of unmanned aerial and ground vehicles in urban and indoor environments

2007

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This paper discusses the integration of Inertial measurements with measurements from a three-dimensional (3D) imaging sensor for position and attitude determination of unmanned aerial vehicles (UAV) and autonomous ground vehicles (AGV) in urban or indoor environments. To enable operation of UAVs and AGVs at any time in any environment a Precision Navigation, Attitude, and Time (PNAT) capability is required that is robust and not solely dependent on the Global Positioning System (GPS). In urban and indoor environments a GPS position capability may not only be unavailable due to shadowing, significant signal attenuation or multipath, but also due to intentional denial or deception. Although deep integration of GPS and Inertial Measurement Unit (IMU) data may prove to be a viable solution an alternative method is being discussed in this paper.The alternative solution is based on 3D imaging sensor technologies such as Flash Ladar (Laser Radar). Flash Ladar technology consists of a modulated laser emitter coupled with a focal plane array detector and the required optics. Like a conventional camera this sensor creates an "image" of the environment, but producing a 2D image where each pixel has associated intensity vales the flash Ladar generates an image where each pixel has an associated range and intensity value. Integration of flash Ladar with the attitude from the IMU allows creation of a 3-D scene. Current low-cost Flash Ladar technology is capable of greater than 100 x 100 pixel resolution with 5 mm depth resolution at a 30 Hz frame rate.The proposed algorithm first converts the 3D imaging sensor measurements to a point cloud of the 3D, next, significant environmental features such as planar features (walls), line features or point features (corners) are extracted and associated from one 3D imaging sensor frame to the next. Finally, characteristics of these features such as the normal or direction vectors are used to compute the platform position and attitude changes. These "delta" position and attitudes are then used calibrate the IMU. Note, that the IMU is not only required to form the point cloud of the environment expressed in the navigation frame, but also to perform association of the features from one flash Ladar frame to the next. This paper will discuss the performance of the proposed 3D imaging sensor feature extraction, position change estimator and attitude change estimator using both simulator data and data collected from a moving platform in an indoor environment. The former consists of data from a simulated IMU and flash Ladar installed on an aerial vehicle for various trajectories through an urban environment. The latter consists of measurements from a CSEM Swissranger 3D imaging sensor and a MicroStrain low-cost IMU. Data was collected on a manually operated aerial vehicle inside the Ohio University School of Electrical Engineering and Computer Science building.

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“…To estimate the rotation matrix, a minimum of two non-parallel planar surfaces is required. It can be shown that equation (10) results in the least squares estimate of R.…”

Section: Attitude Change Estimationmentioning

confidence: 98%

“…For a comprehensive overview of Flash Ladar sensors the reader is referred to [9] [10]. Many early Flash Ladar sensors operate on the principle of measuring the phase difference (shift) between the transmitted and received (from the target) signal from a modulated light/laser.…”

Section: Introductionmentioning

confidence: 99%

Use of 3D laser radar for navigation of unmanned aerial and ground vehicles in urban and indoor environments

2007

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“…Using these values for α and β, the thresholds T 2 and T 1 computed using the expressions in (14) are approximately 4 and −3, respectively.…”

Section: Track Maintenancementioning

confidence: 98%

“…The next generation of ladars will reduce this acquisition time by using scannerless focal plane array (FPA) [14]. Compared with RF, laser radiation is scattered by aerosols and cloud particles, which can limit its operating range.…”

Section: Introductionmentioning

confidence: 99%

A Short-Range Ship Navigation System Based on Ladar Imaging and Target Tracking for Improved Safety and Efficiency

Ruiz

Granja

2009

IEEE Trans. Intell. Transport. Syst.

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A new maritime navigation system based on a laser rangefinder scanner for obstacle avoidance and precise maneuvering operations is described in this paper. The main novelty of this work is the adaptation and implementation of known technology for laser range finding and algorithms for target tracking into a system that operates in real time and has been tested in different natural sea and inland navigation scenarios. The principal components of this system, namely, 1) the laser range finder, 2) the scanning unit, and 3) the data processing and displaying unit, are described in detail. Ladar images are dense horizontally and sparse vertically as a compromise between capturing relevant features and quick frame formation. Images are processed for range outlier removal, and significant observable patterns are extracted. This multiple-target tracking problem is tackled using robust Kalman filtering techniques for continuous tracking of each detected observation. We minimize unreliable track initializations and preserve tracks from deletion during temporal misobservations. The evaluation in open-sea and inland waterways gave good results, making the system valid for precise maneuvering, fluent navigation, and accident mitigation. Objects of interest, from boats to ships, are detected and robustly tracked; pier and lock chamber sketches are reliable; bridge height estimation is precise; and narrow waterways (river banks and bridge columns) are correctly detected. The prototype developed can be considered to be a very valuable complementary device to traditional radar-based techniques that are not totally valid for accurate short-range exploration, improving efficiency and safety in ship operations.

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“…The GDRS ladar has been described in Shneier et al (2003). Other imaging ladar technologies exist; several are described in Juberts and Barbera (2004).…”

Section: Imaging Ladar Technologymentioning

confidence: 99%

Three-Dimensional Change Detection With the Use of an Evidence Grid

Haas¹

2006

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Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing the burden, to Department of Defense, Washington Headquarters Services, Directorate for Information Operations and Reports (0704-0188), 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. REPORT DATE (DD-MM-YYYY) September 20062. REPORT TYPE AUTHOR(S)Gary A. Haas (ARL) 5f. WORK UNIT NUMBER PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) U.S. Army Research Laboratory Weapons and Materials Research Directorate Aberdeen Proving Ground, MD 21005-5066 PERFORMING ORGANIZATION REPORT NUMBER ARL-TR-3916 SPONSOR/MONITOR'S ACRONYM(S) 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) SPONSOR/MONITOR'S REPORT NUMBER(S) DISTRIBUTION/AVAILABILITY STATEMENTApproved for public release; distribution is unlimited. SUPPLEMENTARY NOTES ABSTRACTIn this study, the objective is to find changes in terrain geometry, which are encountered by a patrolling unmanned ground vehicle (UGV) from one patrol run to another. The UGV is equipped with a streaming imaging ladar (laser radar) that measures the distance to the nearest surface at an array of points spanning a prism-shaped field of view and with a navigation system that measures the location of the UGV in a world-fixed coordinate frame. The path followed by the UGV is approximately the same during each run. We are interested in the ability to detect true changes, to reject false alarms, and the range relative to the UGV at which detections occur. SUBJECT TERMS

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Status report on next-generation LADAR for driving unmanned ground vehicles

Cited by 14 publications

References 7 publications

Use of 3D laser radar for navigation of unmanned aerial and ground vehicles in urban and indoor environments

Use of 3D laser radar for navigation of unmanned aerial and ground vehicles in urban and indoor environments

A Short-Range Ship Navigation System Based on Ladar Imaging and Target Tracking for Improved Safety and Efficiency

Three-Dimensional Change Detection With the Use of an Evidence Grid

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