Advanced analytical and control methods for safe and intuitive motion learning of physical interactions with humanoid service robots
Service robots are robots made to work alongside and be of aid to humans in every day environments. These robots must be safe, reliable, and easy to interact without endangering humans nor the environment. The purpose of this partnership aims to develop and implement advanced control methods to enhance the safety and functionality of a class of human-like service robots, called humanoid robots. We first propose a method that enhances a robot’s ability to ensure that it is, in fact, able to detect interaction forces by analyzing the positioning of the robot limbs. Secondly, we plan to implement a method called Learning from Demonstration to allow intuitively teaching the robot new motions through the use of virtual reality headsets and controllers. The learned motions will be further refined by using contextual cues on how to interact with the environment.