An Experimental Study on Pitch Compensation in Pedestrian-Protection Systems for Collision Avoidance and Mitigation

This paper describes an improved stereovision system for the anticipated detection of car-to-pedestrian accidents. An improvement of the previous versions of the pedestrian-detection system is achieved by compensation of the camera's pitch angle, since it results in higher accuracy in the location of the ground plane and more accurate depth measurements. The system has been mounted on two different prototype cars, and several real collision-avoidance and collision-mitigation experiments have been carried out in private circuits using actors and dummies, which represents one of the main contributions of this paper. Collision avoidance is carried out by means of deceleration strategies whenever the accident is avoidable. Likewise, collision mitigation is accomplished by triggering an active hood system

The Analysis of design and manufacturing tasks using haptic and immersive VR - Some case studies

The use of virtual reality in interactive design and manufacture has been researched extensively but the practical application of this technology in industry is still very much in its infancy. This is surprising as one would have expected that, after some 30 years of research commercial applications of interactive design or manufacturing planning and analysis would be widespread throughout the product design domain. One of the major but less well known advantages of VR technology is that logging the user gives a great deal of rich data which can be used to automatically generate designs or manufacturing instructions, analyse design and manufacturing tasks, map engineering processes and, tentatively, acquire expert knowledge. The authors feel that the benefits of VR in these areas have not been fully disseminated to the wider industrial community and - with the advent of cheaper PC-based VR solutions - perhaps a wider appreciation of the capabilities of this type of technology may encourage companies to adopt VR solutions for some of their product design processes. With this in mind, this paper will describe in detail applications of haptics in assembly demonstrating how user task logging can lead to the analysis of design and manufacturing tasks at a level of detail not previously possible as well as giving usable engineering outputs. The haptic 3D VR study involves the use of a Phantom and 3D system to analyse and compare this technology against real-world user performance. This work demonstrates that the detailed logging of tasks in a virtual environment gives considerable potential for understanding how virtual tasks can be mapped onto their real world equivalent as well as showing how haptic process plans can be generated in a similar manner to the conduit design and assembly planning HMD VR tool reported in PART A. The paper concludes with a view as to how the authors feel that the use of VR systems in product design and manufacturing should evolve in order to enable the industrial adoption of this technology in the future

Obstacle Detection Based on Fusion Between Stereovision and 2D Laser Scanner

International audienceObstacle detection is an essential task for mobile robots. This subject has been investigated for many years by researchers and a lot of obstacle detection systems have been proposed so far. Yet designing an accurate and totally robust and reliable system remains a challenging task, above all in outdoor environments. Thus, the purpose of this chapter is to present new techniques and tools to design an accurate, robust and reliable obstacle detection system in outdoor environments based on a minimal number of sensors. So far, experiments and assessments of already developed systems show that using a single sensor is not enough to meet the requirements: at least two complementary sensors are needed. In this chapter a stereovision sensor and a 2D laser scanner are considered

Integrated Stereovision for an Autonomous Ground Vehicle Competing in the Darpa Grand Challenge

The DARPA Grand Challenge (DGC) 2005 was a competition, in form of a desert race for autonomous ground vehicles, arranged by the U.S. Defense Advanced Research Project Agency (DARPA). The purpose was to encourage research and development of related technology. The objective of the race was to track a distance of 131.6 miles in less than 10 hours without any human interaction. Only public GPS signals and terrain sensors were allowed for navigation and obstacle detection. One of the teams competing in the DGC was Team Caltech from California Institute of Technology, consisting primarily of undergraduate students. The vehicle representing Team Caltech was a 2005 Ford E-350 van, named Alice. Alice had been modified for off-road driving and equipped with multiple sensors, computers and actuators. One type of terrain sensors used on Alice was stereovision. Two camera pairs were used for short and long range obstacle detection. This master thesis concerns development, testing and integration of stereovision sensors during the final four months leading to the race. To begin with, the stereovision system on Alice was not ready to use and had not undergone any testing. The work described in this thesis enabled operation of stereovision. It further improved its capability such that it increased the overall performance of Alice. Reliability was demonstrated through multiple desert field tests. Obstacle avoidance and navigation using only stereovision was successfully demonstrated. The completed work includes design and implementation of algorithms to improve camera focus and exposure control, increase processing speed and remove noise. Also hardware and software parameters were configured to achieve best possible operation. Alice managed to qualify to the race as one of the top ten vehicles. However she was only able to complete about 8 miles before running over a concrete barrier and out of the course, as a result of hardware failures and state estimation errors

Structured Light-Based 3D Reconstruction System for Plants.

Camera-based 3D reconstruction of physical objects is one of the most popular computer vision trends in recent years. Many systems have been built to model different real-world subjects, but there is lack of a completely robust system for plants. This paper presents a full 3D reconstruction system that incorporates both hardware structures (including the proposed structured light system to enhance textures on object surfaces) and software algorithms (including the proposed 3D point cloud registration and plant feature measurement). This paper demonstrates the ability to produce 3D models of whole plants created from multiple pairs of stereo images taken at different viewing angles, without the need to destructively cut away any parts of a plant. The ability to accurately predict phenotyping features, such as the number of leaves, plant height, leaf size and internode distances, is also demonstrated. Experimental results show that, for plants having a range of leaf sizes and a distance between leaves appropriate for the hardware design, the algorithms successfully predict phenotyping features in the target crops, with a recall of 0.97 and a precision of 0.89 for leaf detection and less than a 13-mm error for plant size, leaf size and internode distance

IPOL: a new journal for fully reproducible research; analysis of four years development

International audienceAfter four years of development of the Image Processing On Line journal (IPOL), this article presents a first analysis and overview of its scientific and technical development. The main issues met and overcome from the beginning of the journal are described with a focus on the purpose of the journal to establish a state of the art on the main Image Processing topics. The evolution of the online demonstration is also presented with a first analysis of author/publisher criticism, which led to a proposal for a new modular architecture of its demo system

Under vehicle perception for high level safety measures using a catadioptric camera system

In recent years, under vehicle surveillance and the classification of the vehicles become an indispensable task that must be achieved for security measures in certain areas such as shopping centers, government buildings, army camps etc. The main challenge to achieve this task is to monitor the under frames of the means of transportations. In this paper, we present a novel solution to achieve this aim. Our solution consists of three main parts: monitoring, detection and classification. In the first part we design a new catadioptric camera system in which the perspective camera points downwards to the catadioptric mirror mounted to the body of a mobile robot. Thanks to the catadioptric mirror the scenes against the camera optical axis direction can be viewed. In the second part we use speeded up robust features (SURF) in an object recognition algorithm. Fast appearance based mapping algorithm (FAB-MAP) is exploited for the classification of the means of transportations in the third part. Proposed technique is implemented in a laboratory environment