The goal of this project is to enable a robot to actively collaborate with a person to move an object in an efficient and smooth manner. A hurdle in collaboratively moving an object is determining whether the partner is trying to rotate or translate the object (the rotation versus translation problem). For a robot to actively assist a person it is key that the robot recognizes the actions or phases of a collaborative task.
This requires the robot to have the ability to estimate a person’s movement intent.In this project, Hidden Markov Models (HMM) are used to recognize human intent of rotation or translation in real-time using only haptic data measured from robot. Based on this recognition, an appropriate impedance control mode is selected to assist the person. The approach is tested on a seven degree-of-freedom industrial robot, KUKA LBR iiwa 14 R820, working with a human partner during manipulation tasks.