New York: A new study into a robot named “Pepper”, who has been hailed as an emotionally responsive humanoid robot, can help scientists build more affectionate robots.

In her paper, Julienne Greer, an actor, producer, director and theatre arts lecturer at University of Texas, wrote that when humans make a certain gesture such as a smile, it could mean that they are “happy” as well as “angry”.

“Most people only think of engineers and scientists when it comes to robots, which I truly believe will one day be a part of our normal, day-to-day lives,” Greer said.

“With that in mind, don’t we want the people who design this technology to also consider how human beings express feelings and interact with one another in addition to considering how a robot should be wired?” she added.

When Pepper was unveiled in Japan in June 2014, its developer SoftBank said that his company’s aim was to “develop affectionate robots that can make people smile”. Pepper is expected to reach US stores by the summer of 2015.

In her workshops, Greer said that “the categorisation of behaviour or gestures and an understanding of how they create specific emotions in humans will allow the engineers and roboticists to apply those gestures and behaviour to the programming of robots”.

Performance, connection and authenticity are the gold standard that should be hoped for in the creation of the relationship between humans and robots,” Greer added.

“We can attain these goals through the specific application of understanding human behaviour, gesture, shape and relationships. We must be specific in programming robots to respond to, and to eventually to learn from, the human relationships they will be a part of,” she said.

The plan now is for Greer to develop a data-capturing test that would identify the response of humans to robots confronting a variety of circumstances.

Greer presented her paper titled “Building emotional authenticity between humans and robots” at the sixth International Conference on Social Robotics in Sydney, Australia, recently.