Collaborative human-humanoid carrying using vision and haptic sensing

We propose a framework for combining vision and haptic information in human-robot joint actions. It consists of a hybrid controller that uses both visual servoing and impedance controllers. This can be applied to tasks that cannot be done with vision or haptic information alone. In this framework, the state of the task can be obtained from visual information while haptic information is crucial for safe physical interaction with the human partner. The approach is validated on the task of jointly carrying a flat surface (e.g. a table) and then preventing an object (e.g. a ball) on top from falling off. The results show that this task can be successfully achieved. Furthermore, the framework presented allows for a more collaborative setup, by imparting task knowledge to the robot as opposed to a passive follower.