Context Aware Shared Autonomy for Robotic Manipulation Tasks
Bosch Research and Technology Center
Thursday, September 19th, 2013
Abstract: In this talk I will briefly present on-going robotic projects at Bosch (autonomous lawnmower, robot for organic farming, hospital transport assistant system, activities from the PR2 Beta Program) and then describe a project in which a collaborative human-robot system that provides context information to enable more effective robotic manipulation. We take advantage of the semantic knowledge of a human co-worker who provides additional context information and interacts with the robot through a user interface. A Bayesian Network encodes the dependencies between this information provided by the user. The output of this model generates a ranked list of grasp poses best suitable for a given task which is then passed to the motion planner. Our system was implemented in ROS and tested on a PR2 robot. We compared the system to state-of-the-art implementations using quantitative (e.g. success rate, execution times) as well as qualitative (e.g. user convenience, cognitive load) metrics. We conducted a user study in which eight subjects were asked to perform a generic manipulation task, for instance to pour a bottle or move a cereal box, with a set of state-of-the-art shared autonomy interfaces. Our results indicate that an interface which is aware of the context provides beneﬁts not currently provided by other state-of-the-art implementations.
September 19, 2013