Learning redundancy resolution for human-like movements

The kinematically redundant robots pose challenges for human-robot interaction. While these robots provide a great degree of flexibility for the realization of complex applications, criteria for redundancy resolution constraining the robot's movement generation need to be defined. One way of dealing with this configuration challenge is to utilize kinesthetic teaching by guiding the robot to implicitly model the specific constraints in task and configuration space. In order to enable non-experts to master the configuration and programming of a redundant robot, an interaction scheme combining kinesthetic teaching and learning within an integrated system architecture was proposed and evaluated in a user study with 49 industrial workers at HARTING, a medium-sized manufacturing company.

Literature: Wrede et al.