“Robots that work in human environments need to be adaptable to the fact that humans are unique, and that we might all solve the same task in a different way. An important area in robot development, therefore, is to teach robots how to work alongside humans in dynamic environments,” says Maximilian Diehl, Doctoral Student at the Department of Electrical Engineering at the Chalmers University of Technology and the main researcher behind the project.
New explainable Artificial Intelligence (AI)
Although robots require precise programming to work in a constant flow of the same pattern, much more flexible ways of working are required for them to successfully interact with people in areas such as healthcare or customer-facing roles.
To design a humanlike way to approach solving tasks among robots, the study team developed an ‘explainable AI’ (type of artificial intelligence where humans can understand how it arrived at a specific decision or result) that can plan a flexible and adaptable path towards a long-term goal.
“With our AI, the robot made plans with a 92% success rate after just a single human demonstration. When the information from all twelve demonstrations was used, the success rate reached up to 100%.”It might still take several years until we see genuinely autonomous and multi-purpose robots,mainly because many individual challenges still need to be addressed, like computer vision, control, and safe interaction with humans. However, we believe that our approach will contribute to speeding up the learning process of robots, allowing the robot to connect all of these aspects and apply them in new situations”, says Maximilian Diehl.
Source: Medindia
