July - 2015 - issue > CXO View Point

Future of Robots - Artificial Intelligence (AI), Space and The Need For R&D

By Antonio Espingardeiro, Member of IEEE and Robotics Inventor & Researcher
Friday, June 26, 2015
By Antonio Espingardeiro, Member of IEEE and Robotics Inventor & Researcher
IEEE is a non profit organization headquartered in New York. It has over 400,000 members across 160 countries and provides services, conducts conferences, while contributing to important developments in technology and engineering.

Robotics is by its essence a multidisciplinary science. Research into autonomous navigation gathers knowledge from physics, electronics, mechanics and computer science. In the transportation sector, the motivation for developing autonomous vehicles is driven by safer roads, better traffic management systems and energy efficiency. However as technology evolves, there are other types of opportunities arising in the future. In hardware terms autonomous navigation involves high computing power, odometry, sensing technology (GPS, laser ranger finders, ultrasonic, infra-red sensors) and 3D mapping. From a computational point of view (software), autonomous navigation involves pattern recognition, colours, features, shapes, obstacles and continuous statistical analysis for decision making. Such technologies are likely to have a predominant effect on areas such as health and medicine, manufacturing, energy, agriculture, environment or space exploration. In health and medicine, AI and image processing could become determinant tools in the ways health care diagnostics and surgical interventions are performed. Computational algorithms could for example help identifying damaged tissues, and make predictions on what is likely to happen during a biological cycle. Machines are already far superior when it comes to process high volumes of information, and providing alternative diagnostics in health care could become "standard de facto".

Tele robotics will allow new forms of communication, personal advising and motivation which can bridge the gap between care providers and care receivers. In terms of surgical procedures as robots' dexterity and accuracy increases also the ability to assist surgeons in difficult operations will result in better outcomes for both clinicians and patients.

In manufacturing, we could expect image processing to reframe the current production schemes. As computer vision becomes more associated with high levels of dexterity, new forms of production and assembly/disassembly lines could be applied. It is likely that such paradigm will complement factory workers, where robots are better at producing goods but humans are far superior in quality checks, supervision, product design and innovation.

Thirdly, we have energy. Again the notion of computing becomes extremely relevant. As renewable energies become a reality, we will also need to build infrastructures for production/conversion and distribution networks around the globe. The concept here is decentralization. We will use AI, pattern recognition and decision making algorithms to control the flow of energy and bridge the gap between producers and consumers. Such efficient way of controlling energy (intelligent grids) is also likely to broaden the access of energy and eventually reduce the production/conversion/consumption costs.

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