Jun-ichi Takiguchi

GPS Multipath Mitigation for Urban Area Using Omnidirectional Infrared Camera

This paper describes a precision positioning technique that can be applied to vehicles in urban areas. The proposed technique mitigates Global Positioning System (GPS) multipath by means of an omnidirectional infrared (IR) camera that can eliminate the need for invisible satellites [a satellite detected by the receiver but without line of sight (LOS)] by using IR images. Some simple GPS multipath mitigation techniques, such as the installation of antennas away from buildings and using choke ring antennas, are well known. Further, various correlator techniques can also be employed. However, when a direct signal cannot be received by the antenna, these techniques do not provide satisfactory results because they presume that the antenna chiefly receives direct signals. On the other hand, the proposed technique can mitigate GPS multipath, even if a direct signal cannot be received because it can recognize the surrounding environment by means of an omnidirectional IR camera. With the IR camera, the sky appears distinctively dark; this facilitates the detection of the borderline between the sky and the surrounding buildings, which are captured in white, due to the difference in the atmospheric transmittance rate between visible light and IR rays. Positioning is performed only with visible satellites having fewer multipath errors and without using invisible satellites. With the proposed system, static and kinematic evaluations in which invisible satellites are discriminated through observation using an omnidirectional IR camera are conducted. Hence, signals are received even if satellites are hidden behind buildings; furthermore, the exclusion of satellites having large errors from the positioning computation becomes possible. The evaluation results confirm the effectiveness of the proposed technique and the feasibility of highly accurate positioning.

High precision range estimation from an omnidirectional stereo system

This paper presents the estimation of depth based on the cylindrical re-projections of images captured by a stereo setup consisting of two sets of an ODV (omnidirectional vision system). In general, images obtained by such a device have a relatively low spatial resolution and have some aberration in comparison to standard camera images and thus, considerable range estimation errors are caused. We propose a stereo setup of an ODV, which features two mirrors with a contrived curvature to minimize blurring influence. We also propose an edge-based intensity interpolation method, a bi-directional sub-pixel matching procedure, and a discontinuity compensation algorithm to reduce the disparity error.

Development of an Autonomous Mobile Surveillance System Using a Network-based RTK-GPS

This paper describes an autonomous mobile surveillance system usually used in a factory premises with some high-rise buildings. This system consists of a wireless LAN network, a base station and an autonomous vehicle. The vehicle is equipped with a GPS/INS navigation system using the network-based Real-Time Kinematic GPS (RTK-GPS) with Positioning Augmentation Services (PASTM, Mitsubishi Electric Corporation 2003), an Area Laser Radar (ALR), a CCD camera called slaved camera, and an Omni-Directional Vision (ODV) sensor for surveillance and reconnaissance. The vehicle switches navigation modes according to the vehicle status. It has three guidance modes, which are “Normal”, “Road tracking”, and “Crossing recognition”. A field test result shows that the vehicle can track the planned path within 0.10[m] accuracy at straight paths and within 0.25[m] for curved paths even if RTK fixed solutions are not available. Field experiments and analyses have proved that the proposed navigation method can provide good enough guidance accuracy even under poor satellite visibility and that the panorama image database with absolute position is useful for surveillance.

A Mobile Mapping System for road data capture based on 3D road model

The development of road telematics requires the management of continuously growing road database. A MMS(Mobile Mapping System) can acquire this road database, while offering an unbeatable productivity with the combination of navigation, and videogrammetry tools. The proposed MMS, featuring a GPS/DR(Dead Reckoning) combined navigation system, a GPS-Gyro/IMU(Inertial Measurement Unit), laser scanners, nearly horizontal cameras and high sampling rate road data measurement logger, can measure centerline and side-line location precisely considering 3D road surface model based on a laser scanner. The carrier phased D-GPS/DR combined navigation system and GPS-Gyro/IMU performs highly accurate position and posture estimation at a few centimeter and 0.1 degree order. It can be said that the proposed MMS and its unique road signs positioning method is valid and effective as the road sign location error is within 100[mm] even in the slanted road by considering the 3D road surface model.

3D Reconstruction Using Multibaseline Omnidirectional Motion Stereo Based on GPS/Dead-reckoning Compound Navigation System

This paper presents a motion-stereo device using the GPS/DR (dead reckoning) combination along with omnidirectional cameras to reconstruct 3-D environments by means of sensors small enough to be installed on a mobile robot. The proposed technique is based on the fact that it is possible to determine epipolar lines by using the precise positions and heading angles measured by a combination of GPS and various sensors; high-precision stereo matching may then be performed by means of geometrical restrictions. Furthermore, in comparison to the other stereo techniques, it is also possible to establish longer baselines for peripheral objects and simultaneously provide a higher precision in calculating the distances to far objects by applying voting processing to a series of distant motion-stereo images, which can be attained by using more than one baseline length, in 3-D spaces based on the precise positions and heading angles. In short, the proposed technique provides a substantial increase in measurement precision as compared to that with the well-known SFM (structure from motion) technique for reconstructing 3-D environments with monocular cameras; this is because the proposed technique utilizes a greater number of mobile parameters, which are determined using precise cameras. In this experiment, the measurement precision of the proposed technique has been evaluated in reconstructing the shapes of vehicles parked alongside a road; the measurements were found to have a standard deviation of 140 mm within a range of 10 m. It can be stated that the proposed omnidirectional motion-stereo technique is robust to environmental perturbations and can accurately estimate distances in the case of highly textured objects.

GPS accuracy improvement by satellite selection using omnidirectional infrared camera

This paper describes a precision positioning technique that can be applied to vehicles in urban areas. The proposed technique mitigates GPS multipath by means of an omnidirectional infrared (IR) camera that can eliminate the need for invisible satellites (a satellite detected by the receiver but without LOS (Line Of Sight)) by using IR images. Some simple GPS multipath mitigation techniques such as installation of antennas away from buildings and using choke ring antennas are well known. Further, various correlator techniques can also be employed. However, when a direct signal cannot be received by the antenna, these techniques do not provide satisfactory results because they presume that the antenna chiefly receives direct signals. On the other hand, the proposed technique can mitigate GPS multipath even if a direct signal cannot be received because it can recognize the surrounding environment by means of an omnidirectional IR camera. With the IR camera, the sky appears distinctively dark; this facilitates the detection of the borderline between the sky and the surrounding buildings, which are captured in white, due to the difference in the atmospheric transmittance rate between visible light and the IR rays. Positioning is performed only with visible satellites having less multipath errors, and without using invisible satellites. With the proposed system, static and kinematic evaluations in which invisible satellites are discriminated through observation using an omnidirectional IR camera are conducted. Hence, signals are received even if satellites are hidden behind buildings; furthermore, exclusion of satellites having large errors from the positioning computation becomes possible. The evaluation results confirm the effectiveness of the proposed technique and the feasibility of highly accurate positioning.

A study of precise road feature localization using mobile mapping system

In the near future, precise digital map data is said to be applied to the next generation car navigation system as well as ITS to increase the driving safety. It is important to maintain digital map datas freshness and accuracy. A MMS (Mobile Mapping System) can acquire this highway database, while offering unbeatable productivity with the combination of navigation and videogrammetry tools. The proposed MMS, featuring a GPS/DR combined navigation system, a GPS-Gyro/IMU, nearly horizontal cameras, laser scanners, high sampling rate road data measurement logger, and the network-based RTK-GPS PAStrade can acquire road feature location like snow-poles, guard-rails, road signs and road line precisely at normal cruising speed considering 3D road surface model. The carrier phased D-GPS/DR combined navigation system and GPS-Gyro/IMU performs highly accurate positioning performance at a few centimeter and posture estimation at 0.073 [deg rms] for heading and 0.064 [deg rms] for pitching, and 0.116 [deg rms] for rolling. Furthermore, the proposed road feature digitizing method, featuring 2D camera image projection to the 3D road surface model, allows users to understand complicated 3D point-cloud data intuitively and to designate desired road feature with few mistakes. The accuracy comparison between the static RTK-GPS/Total-Station measurement with the dynamic MMS mobile measurement reveal that the system allows 0.3 [m] road feature measurement accuracy with unbeatable productivity when sufficient GPS visibility is obtained.

Development of a vehicle-mounted road surface 3D measurement system

In recent years, automation system based on IT technology becomes very popular not only for manufacturing industries but also for the construction and civil engineering industries. The conventional location survey method in the civil engineering construction site is pinpoint location survey for a broad objective area. The conventional method has severe constraints when it comes to measure the broad objective area as macro or to estimate general distinctive geometrical features. In this study, a unique vehicle-mounted mobile measurement system which can measure dense 3D point-cloud data for wide construction site is presented. The proposed MMS (Mobile Mapping System) is equipped with the carrier phased D-GPS/DR combined navigation system, the GPS gyro, and a laser scanner. The MMS, which measures unleveled round surface at 40 (km/h) using laser scanners range data and vehicle attitude stabilization algorithm, can construct continuous dense road surface 3D model. The functional and performance test as a mobile measurement instrument is revealed. Keywords GPS-Gyro/IMU, Mobile Mapping System, as-built management, 3D mesurement

Development of a positioning technique for an Urban area using omnidirectional infrared camera and aerial survey data

This paper describes an outdoor positioning system for vehicles that can be applied to an urban canyon by using an omnidirectional infrared (IR) camera and a digital surface model (DSM). By means of omnidirectional IR images, this system enables robust positioning in urban areas where satellite invisibility caused by buildings hampers high-precision GPS measurements. The omnidirectional IR camera can generate IR images with an elevation of 20–70° for the surrounding area of 360°. The image captured by the camera is highly robust to light disturbances in the outdoor environment. Through the IR camera, the sky appears distinctively dark; this enables easy detection of the border between the sky and the buildings captured in white due to the difference in the atmospheric transmittance rate between visible light and IR rays. The omnidirectional image, which includes several building profiles, is compared with building-restoration images produced by the corresponding DSM in order to determine the self-position. Field experiments in an urban area show that the proposed outdoor positioning method is valid and effective, even if high-rise buildings cause satellite blockage that affects GPS measurements.

Development of a forward-hemispherical vision sensor for acquisition of a panoramic integration map

The target of this research is to develop a common-use sensor which is useful for navigation and mission for rescue operation. By combined use of an ODV (omnidirectional vision) with a hemispherical forward-visual-field using a direct and reflection hybrid optical system, a RTK-GPS (real time kinematics-global positioning system) and a MEMS (micro electro mechanical systems) IMU (inertial measurement unit), this sensor outputs a realtime image for remote control of a mobile robot and a panoramic integration map, including information on three-dimensional own-position, with a continuous panoramic image for searching victims and for making a rescue plan. The evaluation of the panoramic integration map and the Kalman filter based self-positioning reveals that the proposed method is valid and effective