Take a brave step forward by finding discovering the technological and engineering breakthroughs illustrated in Episode 1: Machines
Aim: Create a robotic car which doesn't need a human driver and can operate safely amongst other vehicles on public roads
Who: Chris Urmson - Google car chief engineer
Sebastian Thurn - Professor of computer science at Stanford University
Organisations: Google & Stanford University artificial intelligence lab
Country: USA, California
Global Impact: Replacing drivers with robots removes the possibility of human error, leading to a reduction in accidents and saving lives. The cars increase efficiency and would free up drivers for other tasks.
The Future: These cars can cope with complicated road conditions and if introduced on a large scale they would drive closer together than human drivers with no lapses in concentration. Chris Urmson suggests that this efficiency improvement would mean no new roads would need to be built for thirty years.
Area of Science: Brain-computer interface
Aim: Control machines using input from the human brain
Who: José del R. Millán - Associate professor of non-invasive brain-computer interface
Organisation: École Polytechnique Fédérale de Lausanne
Country: Switzerland, Lausanne
Global Impact: These machines can be used after a short period spent learning the shared control system. There is a prospect for paralysed or severely disabled people to use systems like this to gain mobility.
The Future: Professor Millán believes that systems like this will be used by astronauts for safe low gravity work as an augmentation to their own abilities. Perhaps systems like these will also be used in our homes to control appliances.
Area of Science: Robotic learning
Aim: Create a robot that can learn like a human
Who: Giulio Sandini - Professor of bioengineering and director of the iCub project
Georgio Metta - Senior scientist on the iCub project
Organisation: Italian Institute of Technology
Country: Italy, Genoa
Global Impact: Robots which can learn by experience give scientists a testing ground for artificial intelligence and help us understand how humans learn
The Future: The development of robot systems like iCub is leading to more complex systems which can learn from humans in the same way that humans learn from each other. A longer term prediction is that we will eventually see learning robots which can work and live among us and respond independently to the world.
Area of Science: Robotic exoskeleton
Aim: Rehabilitation of people who have lost the ability to walk
Who: Dr Alberto Esquenazi - specialty: Physical Medicine and Rehabilitation
Organisation: Moss Rehabilitation Centre of the Albert Einstein Healthcare Network
Country: USA, Philadelphia
Global Impact: The exoskeleton gives the ability to walk back to those who have lost it through accident or disease. It works by detecting the user's sensory input so it is not tiring to use and could realistically be worn all day.
The Future: The system is still only used in the hospital but once it has been developed and trialled comprehensively paraplegic patients could train to use systems like this and regain their independence.
Area of Science: High resolution telescopy
Aim: Detect exoplanets (planets outside our solar system)
Who: Riccardo Scarpa - Professor of astrophysics
Organisation: Gran Telescopio CANARIAS (GTC)
Country: Canary Islands (Spain)
Global Impact: The GTC has the ability to detect Earth sized planets elsewhere in the universe. As planets pass over a distant star they reduce the light received at the GTC and by studying the change of signal scientists can determine a newly discovered planet's chemical composition and orbit.
The Future: No Earth sized planets have been detected yet, but in future planets of this size may be found as the technique improves and the search continues. This may reveal similar atmospheric conditions to Earth elsewhere in the universe.