Interacting in time and space: Investigating human-human and human-robot joint action

Abstract

When we have to physically interact with a robot, the benchmark for natural and efficient performance is our experience of daily interactions with other humans. This goal is still far despite significant advances in human-robot interaction. While considerable progress is made in various areas ranging from improving the hardware over safety measures to better sensor systems, the research on basic mechanisms of interaction and its technical implementation is still in its infancy. In the following, we give an overview of our own work aiming at improving human-robot interaction and joint action. When humans jointly collaborate to achieve a common goal, the actions of each partner need to be properly coordinated to assure a smooth and efficient workflow. This includes timing of the actions, but also, in the case of physical interaction, the spatial coordination. We thus first investigated how a simple physical interaction, a hand-over task between two humans without verbal communication, is achieved. Our results with a human as receiver and both humans and robots as delivering agent show that both the position and the kinematics of the partner's movement are used to increase the confidence in predicting hand-over in time and space. These results underline that for successful joint action the robot must act predictably for the human partner. However, in a more realistic scenario, robot and human constitute a dynamic system with each agent predicting and reacting to the actions and intentions of the other. We therefore investigated and implemented an assembly task where the robot acts as assistant for the human. Using a Bayesian estimation framework, the robot predicts assembly duration in order to deliver the next part just in time.