Jun-ichi Meguro

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.

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 Small UAV for Immediate Hazard Map Generation

An unmanned aerial vehicle (UAV) system providing quick response imagery for natural disaster assessment was developed. A prototype UAV and on-board software using a GPS navigation system were developed for this purpose. The flight performance was evaluated by 6DOF simulations and rigorous flight tests. In the proposed system, collected images by an on-board digital camera is transmitted in real-time to a spatial temporal GIS to share the information. The usability of the small UAV system was qualified by a flight experiment in a city-wide emergency evacuation drill.

Real-time hazard map generation using small unmanned aerial vehicle

This paper presents a disaster mitigation system that uses a small unmanned aerial vehicle (UAV). The immediate assessment of damage and the continuous collection of information when natural disasters such as large earthquakes strike are important for developing a disaster recovery plan for damage mitigation. In this study, we develop a small prototype UAV and onboard software using a GPS navigation system and propose a unique disaster mitigation system that generates digital real-time hazard maps with the aid of the UAV. The effectiveness of the proposed system is confirmed by a flight experiment.

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.

Automatic lane-level map generation for advanced driver assistance systems using low-cost sensors

Lane-level digital maps can simplify driving tasks for robotic cars as well as enhance performance and reliability for advanced driver assistance systems (ADAS) by providing strong priors about the driving environment. In this paper, we present a system for automatic generation of precise lane-level maps by using conventional low-cost sensors installed in most of current commercial cars. It mainly consists of two modules, i.e. road orthographic image generation and lane graph construction. First, we divide the global map into fixed local segments based on the road network topology. According to the local map segments, we accumulate the birds eye view images of the road surface by fusing GPS, INS and visual odometry, and subsequently integrate them into synthetic orthographic images with the reference of the local map segments. Furthermore, the information of the driving lanes is extracted from the orthographic images and a large amount of vehicle trajectories, which is used to construct the lane graph of the map based on the lane models we proposed. Such a system can offer increased value as well as promote the automation level for todays commercial cars without being supplemented additional sensors. Experiments show promising results of the automatic map generation of the real-world roads, which substantiated the effectiveness of the proposed approach.

Rescue Infrastructure for Global Information Collection

In the disaster situation, it is important to collect quickly global information on the disaster area and victims buried in the debris and waiting for rescue. In the DDT project (special project for earthquake disaster mitigation in urban areas), the research and development on rescue infrastructure for global information collection have been carried out. In the activity of the mission unit for infrastructure, ubiquitous handy terminal devices have been and technology for forming an ad-hoc wireless communication network have been developed as well as technology to integrate the collected information on the GIS system including communication protocol design. In this paper, the current R&D activities of the mission unit for infrastructure in the DDT project are overviewed, and some technologies developed so far are introduced

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 Multimodal ADAS System for Unmarked Urban Scenarios Based on Road Context Understanding

Comprehensive situational awareness is paramount to the effectiveness of advanced driver assistance systems (ADASs) used in daily urban traffic, particularly for the unmarked roads, which cannot fulfill the requirements of conventional ADAS systems. This paper proposed a stereovision-based multimodal ADAS system designed for expanding the usability of ADAS functions, including lane-keeping assist, adaptive cruise control, and precrash system, to normal urban scenarios with unmarked roads. At first, the physical road boundary and vehicle candidates are detected. Subsequently, the contextual information between the host vehicle, the road, and the other vehicles are correlated for both low-level object detection improvement and high-level road structure estimation. Finally, the required ADAS elements are generated based on the correlation results with respect to the system functionalities. Experimental results in various typical but challenging scenarios have substantiated the effectiveness of the proposed system, which could help increase the value of the existing ADAS system without major modifications or expense.

Improved Lane Detection Based on Past Vehicle Trajectories

Knowing where the host lane lies is paramount to the effectiveness of many advanced driver assistance systems (ADAS), such as lane keep assist (LKA) and adaptive cruise control (ACC). This paper presents an approach for improving lane detection based on the past trajectories of vehicles. Instead of expensive high-precision map, we use the vehicle trajectory information to provide additional lane-level spatial support of the traffic scene, and combine it with the visual evidence to improve each step of the lane detection procedure, thereby overcoming typical challenges of normal urban streets. Such an approach could serve as an Add-On to enhance the performance of existing lane detection systems in terms of both accuracy and robustness. Experimental results in various typical but challenging scenarios show the effectiveness of the proposed system.