We are increasingly dependent on an increasingly unknown system, the internet. It has an expanding attack surface and is constantly evolving and changing, at a rate that is showing no sign of easing. Ironically, it presents both a critical security challenge and a great opportunity. With such a complex, multifaceted and fast-changing technological area, we cannot hope to successfully meet the challenges and accept the opportunities without broadly partnering. Put simply, it is a case of ‘partner or perish’. Or is that ‘partner and prosper’? This paper explores the contemporary cyber context and discusses the approach taken by the Australian Government’s Defence Science and Technology Group in establishing its cyber science and technology programme, and its approach to partnerships as a critical enabler.

A method of determining an eye gaze direction of an observer is disclosed comprising the steps of: (a) capturing at least one image of the observer and determining a head pose angle of the observer; (b) utilizing the head pose angle to locate an expected eye position of the observer, and (c) analyzing the expected eye position to locate at least one eye of the observer and observing the location of the eye to determine the gaze direction.

This chapter describes the emerging robotics application field of intelligent vehicles - motor vehicles that have autonomous functions and capabilities. The chapter is organized as follows. Section 62.1 provides a motivation for why the development of intelligent vehicles is important, a brief history of the field, and the potential benefits of the technology. Section 62.2 describes the technologies that enable intelligent vehicles to sense vehicle, environment, and driver state, work with digital maps and satellite navigation, and communicate with intelligent transportation infrastructure. Section 62.3 describes the challenges and solutions associated with road scene understanding a key capability for all intelligent vehicles. Section 62.4 describes advanced driver assistance systems, which use the robotics and sensing technologies described earlier to create new safety and convenience systems for motor vehicles, such as collision avoidance, lane keeping, and parking assistance. Section 62.5 describes driver monitoring technologies that are being developed to mitigate driver fatigue, inattention, and impairment. Section 62.6 describes fully autonomous intelligent vehicles systems that have been developed and deployed. The chapter is concluded in Sect. 62.7 with a discussion of future prospects, while Sect. 62.8 provides references to further reading and additional resources.

Joe Engelberger, the pioneer of the robotics industry, wrote in his 1989 book Robotics in Service that the inspiration to write his book came as a reaction to an industry-sponsored forecast study of robot applications, which predicted that in 1995 applications of robotics outside factories - the traditional domain of industrial robots - would amount to less than 1% of total sales. Engelberger believed that this forecast was very wrong, and instead predicted that the non-industrial class of robot applications would become the largest class. Engelbergers prediction has yet to come to pass. However, he did correctly foresee the growth in non-traditional applications of robots. Robots are now beginning to march from the factories and into field and service applications. This book presents a selection of papers from the first major international conference dedicated to field and service applications of robotics. This selection includes papers from the leading research laboratories in the world together with papers from companies that are building and selling new and innovative robotic technology. It describes interesting aspects of robots in the field ranging from mining, agriculture, construction, cargo handling, subsea operations, removal of landmines, to terrestrial exploration. It also covers a diverse range of service applications, such as cleaning, propagating plants and aiding the elderly and handicapped, and gives considerable attention to the technology required to realise robust, reliable and safe robots.

Advanced Driver Assistance Systems (ADAS) provide warnings and in some cases autonomous actions to increase driver and passenger safety by combining sensor technologies and situation awareness. In the last 10 years progressed from prototype demonstrators to full product deployment in motor vehicles. Early ADAS examples include Lane Departure Warning (LDW) and Forward Collision Warning (FCW) systems have been developed to warn drivers of potentially dangerous situations. More recently, driver inattention systems have made their debut. These systems are tackling one of the major causes of fatalities on roads – drowsiness and distraction. This paper describes DSS, a driver inattention warning system which has been developed by Seeing Machines for commercial applications, with an initial focus on heavy vehicle fleet management applications. A case study reporting a year-long real-world deployment of DSS is presented. The study showed the effectiveness of the DSS technology in mitigating driver inattention in a sustained manner.

The contents of this book are suitable for the engineers and technicians in the fields of automatic machines and robotics, developers of applications for multiaxes machines and robot cells, and students of electrical and mechanical engineering courses.

Current road safety initiatives are approaching the limit of their effectiveness in developed countries. A paradigm shift is needed to address the preventable deaths of thousands on our roads. Previous systems have focused on one or two aspects of driving: environmental sensing, vehicle dynamics or driver monitoring. Our approach is to consider the driver and the vehicle as part of a combined system, operating within the road environment. A driver assistance system is implemented that is not only responsive to the road environment and the driver's actions but also designed to correlate the driver's eye gaze with road events to determine the driver's observations. Driver observation monitoring enables an immediate in-vehicle system able to detect and act on driver inattentiveness, providing the precious seconds for an inattentive human driver to react. We present a prototype system capable of estimating the driver's observations and detecting driver inattentiveness. Due to the "look but not see" case it is not possible to prove that a road event has been observed by the driver. We show, however, that it is possible to detect missed road events and warn the driver appropriately.

Perception in the visual cortex and dorsal stream of the primate brain includes important visual competencies, such as: a consistent representation of visual space despite eye movement; egocentric spatial perception; attentional gaze deployment; and, coordinated stereo fixation upon dynamic objects. These competencies have emerged commensurate with observation of the real world, and constitute a vision system that is optimised, in some sense, for perception and interaction. We present a robotic vision system that incorporates these competencies. We hypothesise that similarities between the underlying robotic system model and that of the primate vision system will elicit accordingly similar gaze behaviours. Psychophysical trials were conducted to record human gaze behaviour when free-viewing a reproducible, dynamic, 3D scene. Identical trials were conducted with the robotic system. A statistical comparison of robotic and human gaze behaviour has shown that the two are remarkably similar. Enabling a humanoid to mimic the optimised gaze strategies of humans may be a significant step towards facilitating human-like perception.

IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING is published by the IEEE Robotics and Automation Society. All members of the IEEE are eligible for membership in the Society and will receive this TRANSACTIONS upon payment of the annual Society membership fee of $9.00 plus an annual subscription fee of $50.00. For information on joining, write to the lEEE Service Center at the address below. Member copies of Transactions/Journals are for personal use only.

This is an introductory textbook for teachers, students, professionals, and hobbyists who want to learn the basics of computer vision. The book is completely based around the OpenCV library, an open source project that started in 1999 by the computer-vision community. The authors of the text are among the principal contributors to this real-time library that has developed in C/C++ to run Linux, Windows, and Mac OS X. Although it is unashamedly a promotion for the open-source library, it is still a worthy educational text.

Today, we expect that all consumer technologies such as computers, ipods and motor vehicles all operate with the highest levels of performance, reliability and integrity. For robotics and automation technologies to successfully deployed into everyday situations, the general public quite rightly expect automation systems to be fully operational 100% of the time. People expect autonomous technologies to operate at higher levels of performance and safety than people themselves exhibit. For example smart car technologies are expected to cause ZERO accidents while human errors kill more 150,000 people on our roads world-wide every year!

Since 2005, the IEEE Robotics and Automation Society and International Federation of Robotics (IFR) have cooperated to host a joint Forum of Innovation and Entrepreneurship in Robotics and Automation to foster cooperation between the scientific community and industry. As part of the forum, an award for Invention and Entrepreneurship in Robotics and Automation (IERA) is made. This year the IEEE--IFR form was held in Kobe, Japan, in conjunction with the IEEE International Conference on Robotics and Automation (ICRA) 2009.

Introducing a new approach to intelligent vehicle systems. Previous systems have focused on one or two aspects of: environmental sensing, vehicle dynamics or driver monitoring. Our approach is to consider the driver and the vehicle as part of a combined system, operating within the road environment. A driver assistance system is implemented that is not only responsive to the road environment and the driver's actions but also designed to correlate the driver's gaze with the road scene to determine the driver's observations. Driver observation monitoring enables the system to anticipate the driver's needs, enabling: context relevant information selection, redundant information suppression and a natural acknowledgement interface.

This article summarizes current work in Australian robotics research. We outline the work in progress at the major research groups across Australia and draw themes emerging in Australian research. We focus on research groups rather than on industrial robotics.