Semi-autonomous initial monitoring for context-aware task planning

In this paper the semi-autonomous initial monitoring concept for the care-providing robotic system FRIEND is presented. The objective of this concept is context-aware task planning, i.e. the planning procedure is adapted to the actual situation which is the initial situation for the next task, so that the system is able to operate in an intelligent manner also in unknown environments. Therefore the states and the relationships of the task related objects are symbolically described using Boolean values, called facts. All these values have to be determined to identify the initial situation. The user can be included in the determination process to guarantee a successful task planning even if the system fails and an autonomous execution would therefore not possible. A proper heuristic is presented to find the optimal order for the facts determination which minimizes the amount of user interactions. Feedback from the past is used as well as an inference machine which is able to conclude unspecified facts without any further calculation from already known ones. The performance of the initial monitoring concept is evaluated through experimental results, which show that the costs and the user involvement is reduced significantly.