The above are some instances of notable developments in autonomous systems that signify the growing interest in the use of these systems in many domains. To obtain a better understanding of the functional and operational requirements of these systems when deployed in real environments, social and technological factors driving this interest are identified as follows:
(a) (b) (c) (d)
Figure 1.2: Examples of service and assistive robots. Service and assistive robotics are gradually becoming a part of everyday life. (a) The Honda ASIMO humanoid robot. (b) Hitachi’s EMIEW service robot. (c) Sony’s QRIO entertainment robot. (d) iRobot Roomba vacuum cleaner robot.
Social drivers
Demographic changes and advances in healthcare have meant an increase in the elderly population to the possible extent that, within the next two decades, the age pyramid would likely be reversed, i.e. the number of elderly people would be higher than those of working age, especially in developed countries. As the former would have reduced physical capabilities, initiatives for using autonomous systems as healthcare assistants are gaining momentum. Energy shortages and ecological awareness are placing increasing pressures on the overall reduction of pollutants and energy usage in all aspects of human activity. Consequently, automobile manufacturers are looking into the use of vehicle guidance systems and navigation tools to optimize the use of energy while at the same time enhancing the safety of the passengers and other road users.
Autonomous systems are being envisioned to address several of these needs. Intelli- gent Transportation Systems (ITS) are currently in development to reduce the number of privately-owned vehicles on the roads, and economize on the number of passengers conveyed per unit energy expended. The use of electric-powered vehicles with next- generation, green power systems (such as fuel cells) would reduce the dependency on fossil fuels. With the pressures of an aging population, domestic robotic assistants may look after the ill or elderly within the household, surgery robots may assist surgeons in performing delicate operations, and robotic toys capable of portraying different emotions may fulfil psychological or companionship needs of human beings (especially those who are childless, and the elderly) as a soft form of rehabilitation.
Heightened security concerns in response to the threats posed by terrorism and war- fighting efforts (Carrolla et al., 2005; Singh and Thayer, 2001), together with search and rescue operations in the aftermath of natural and man-made disasters (Murphy, 2004), are areas which are driving efforts for effective solutions based on autonomous systems. For instance, since 2003, more than 330 EOD robots have been shipped to Iraq and Afghanistan (Karlin, 2007). While the potential for military applications continue to be a key driver for the development of autonomous systems, robots are increasingly being required for performing reconnaissance and surveillance in civilian settings, for instance, as part of rescue and reparation efforts in the aftermath of hurricane Katrina in 2005 where unmanned aerial vehicles (UAVs) were deployed in the face of severe limitations (Carlson and Murphy, 2005; Willmott, 2005).
Technological drivers
Enabling technologies present opportunities for the application of research and develop- mental success into both existing and novel niche areas. The convergence of advances in information and communication technologies (ICT) in recent years is providing the means for the deployment of autonomous systems. The exponential growth of computing power is providing the opportunity for computationally-intensive processes to be run real-time (Bertozzi et al., 1996; Hassan et al., 2001; Montemerlo et al., 2003; Wang et al., 2000). Progress in communication systems has led to greater mobility, with the emergence of distributed or collaborative systems where simpler entities can evolve and interact withinintelligent spaces, sharing information gathered by their distributed sensors (Jung and Zelinsky, 1999; Kogut et al., 2003). Increasingly, computation can be performed on-board, using lightweight computational devices (Garcia and Valavanis, 2006; Valavanis et al., 2005). The miniaturization of such devices paves the way for autonomous systems with greater mobility and smaller form-factors (Barnes et al., 2005; Bruch et al., 2005). Progress in sensor systems and computer vision have led to an increase in machine perception capability (Brown et al., 2003; Dickmanns, 1998;
Sukkarieh et al., 1999; Wagner et al., 2002), resulting in their pervasive use in current autonomous platforms (Bertozzi et al., 2006; Kelly and Stenz, 1998; Thrun et al., 2006). The combination of these technologies is enabling the deployment of autonomous systems in environments of increasing sophistication.
Command Interpretation
Behaviour-based Intelligence Autonomous Task Planning
Reasonable Thinking Human-like Intelligence Today
1-2 years 3-5 years 6-10 years 11-20 years 21-50 years 51-100 years
Figure 1.3: Technology roadmap for development of intelligent systems. European Robotics Research Network (EURON) GROWTH ProRobot Project (Dario et al., 2004).
Convergence of social and technological drivers
Given the social and technological drivers delineated above, there are strong needs for the development of autonomous systems with capabilities exceeding those which are currently available. At the same time, there is enabling technology available in the form of sensors, processing capability, software and analysis tools to pursue the development of autonomous systems with useful capabilities. These include the ability to perceive and interact independently with the environment, exhibit higher levels of intelligence and adaptability, deeper levels of planning and task execution, and with stronger abilities to interact effectively with other entities within the workspace. Such capabilities can potentially be brought about by modelling human capabilities in order to impart these features to autonomous systems.
Despite the alignment of social and technological drivers, further research is expected before fully autonomous capabilities can be attained, as indicated in a technology roadmap for the development of intelligent systems in Figure 1.3 (Dario et al., 2004).
While striving for autonomous systems with human-like intelligence, several interme- diate milestones have to be reached. Furthermore, progress towards behaviour-based intelligence in artificial systems is expected to be achieved only in the next decade.