Interactive symbol generation of task planning for daily assistive robot

Abstract

For the development of both hardware and software, task plannings become more and more important for robots to perform various tasks. Applying task planning to robotic system for working in real environments has difficulties. Estimating required symbols before planning is difficult because real environments are partially observable. In this paper, we proposed a method for task planning in partially observable environments with unknown objects. To construct conditional plans used in these environments, we extend the description of actions to multi-effect actions, and to deal with unknown objects, robots get new symbols generated by human interaction on demand. Additionally we show experiments of Willow Garage's PR2 executing the task in the real environment with unknown objects.