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Imagine having your own humanoid robot. It is great at its job so your floors and windows are gleaming and spotless, but it has an annoying habit of vacuuming the living room when you have a headache, or offering you a meal just as you are drifting off to sleep on the sofa.

If you sometimes have difficulty reading other people鈥檚 expressions and emotions, imagine how difficult it will be for silicon-brained robots. They will only ever be able to respond to us in an appropriate way if they can understand human moods.

What robots need is kansei. The Japanese term encompasses a raft of emotional notions, including feeling, mood, intuitiveness and sensibility. Without kansei, says Shuji Hashimoto, director of the humanoid robotics centre at Waseda University in Tokyo, the service robots being developed around the world will not be able to acquire the social skills they will need to get along with tetchy, emotional humans.

Last week Hashimoto told a conference on socially intelligent robots at the University of Hertfordshire in Hatfield, UK, that unless researchers start incorporating such emotional concepts into their robots鈥� programming we will be interacting with some pretty insensitive brutes in our living rooms. 鈥淓motion is one of the most crucial factors influencing the success or failure of communication between humans,鈥� he says. 鈥淩obots are going to need similar emotional capabilities if they are to cooperate smoothly and flexibly with humans in our residential environments.鈥�

Hashimoto sees emotive robotics engineering as an essential follow-up to the brute force of today鈥檚 artificial-intelligence-based programming techniques, in which simple rules are applied to signals generated by a robot鈥檚 sensors. For instance, when one of today鈥檚 floor-crawling robotic vacuum cleaners senses it has reached the wall, its computer brain knows it is time to cut its motor and set a new course. Its AI simply pairs sensed situations with a set of pre-programmed actions.

Generating an appropriate response to someone鈥檚 mood is a much more complicated task, so kansei-enabled robots will need to make use of sensors worn by their owner to spot signs of stress. These could include galvanic skin sensors that detect sweat by measuring the conductivity of the skin, and pulse monitors. Neural networks, which can interpret large amounts of data, will then be able to decide how best to react to the person. Hashimoto鈥檚 hope is that in this way robots will at least appear capable of intuitive behaviour. So if a robot鈥檚 owner is sweating and has a racing pulse, say, the robot will sense this and decide that now might not be the time to offer them the TV guide or tonight鈥檚 dinner menu.

鈥淚f a person is stressed, the robot will decide now is not the time to bring the TV guide鈥�

This is no pipe dream, says Elizabeth Croft, a robotics researcher at the University of British Columbia in Vancouver, Canada. She says researchers are already using such physiological sensors alongside face and gesture recognition systems to study the emotional state of people when a robot is present. Her group has monitored how volunteers interact with a robot while they are wired-up with skin conductance, heart rate and facial muscle sensors (see 鈥淪ensors and sensibility鈥�). They found that the very arrival of a robot can be enough to affect people. 鈥淭he behaviour of the robot elicits a measurable physiological response from the user, such as surprise, calm, fear or interest. We can integrate this information into the robot鈥檚 controller to allow the robot to respond in an appropriate manner,鈥� she says.

鈥淭he very arrival of a robot can be enough to affect the way that people behave鈥�

Hashimoto admits that even this level of complexity is merely technological play-acting. 鈥�Kansei robots will seem to understand human feeling to some extent and will appeal to us with their reactions. But they are not machines with a heart; they just look like they have a heart.鈥�

Faking it this way is not only philosophically unattractive to roboticists but also has a serious engineering downside: the more a robot attempts to cater for every conceivable human emotional state with appropriate reactions, the more complex its software becomes. This will ultimately make programming robots an immensely complex process, and render their software dangerously untestable.

One way around this programming nightmare, Hashimoto suggests, would be to let robots learn from their environment and construct their own sets of rules. This would force some robotics researchers to free themselves from the self-imposed shackles of the late Isaac Asimov鈥檚 three 鈥渓aws鈥� of robotics. Coined in a 1942 short story called Runaround, these laws impose heavy constraints on a robot鈥檚 software. Asimov鈥檚 first law says that robots cannot harm a human or let a human come to any harm; the second says robots must always obey humans, unless that infringes the first law; and the third says robots must always protect themselves, unless that infringes the first or second laws. These rules demand enormous complexity from a robot鈥檚 software, as every new situation must take them into account.

Instead of instilling this 鈥渕oral framework鈥� from the outset, Hashimoto thinks a robot鈥檚 intelligence should grow as it ages, learning through trial and error much like a child goes from babyhood through to toddling and eventually to adolescence. 鈥淲e have to design environments where human and robot learn together,鈥� Hashimoto says. Such a move would be controversial, placing robots in many ways on a par with humans. 鈥淏ut humans should not stand at the centre of everything. We need to establish a new relationship between human and machine.鈥�

Ditching Asimov would be a major wrench for robot makers, particularly those developing safety-critical domestic service robots, but Hashimoto is sticking to his guns: 鈥淎s long as we obey Asimov鈥檚 laws, we will never have a machine that is a true partner for a human,鈥� he says.