Abstract
Embodied artificial agents operating in dynamic, real-world environments need architectures that support the special requirements that exist for them. Architectures are not always designed from scratch and the system then implemented all at once, but rather, a step-wise integration of components is often made to increase functionality. In order to increase flexibility and robustness, a task planner was integrated into an existing architecture and the planning process was coupled with the pre-existing execution and the basic monitoring processes. This involved the conversion of monolithic SMACH scenario scripts (state-machine execution scripts) into modular states that can be called dynamically based on the plan that was generated by the planning process. The procedural knowledge encoded in such state machines was used to model the planning domain for two RoboCup@Home scenarios on a Care-O-Bot 3 robot. This was done for the JSHOP2 hierarchical task network (HTN) planner. A component which iterates through a generated plan and calls the appropriate SMACH states was implemented, thus enabling the scenarios. Crucially, individual monitoring actions which enable the robot to monitor the execution of the actions were designed and included, thus providing additional robustness.
About the authors
Elizaveta Shpieva obtained a Master's degree in Autonomous Systems from the Bonn-Rhein-Sieg University of Applied Sciences (BRSU) and a Master's degree and first degree in Computer Engineering and Computer Science from Moscow State Technical University Moscow Institute of Radioengineering, Automatics and Electronics. During her studies at BRSU, she participated in two projects: Russian-German Year of Education, Science and Innovation 2011/12 and Filling the Educational Gap in Service Robotics(Edufill). Currently, she is working for the Russian robotics company Rbot.
Bonn-Rhein Sieg University of Applied Science
Iman Awaad received her Bachelor's degree in Computer Science from Rutgers University, USA in 1996 and a Master's degree in Autonomous Systems from the Bonn-Rhein-Sieg University of Applied Sciences (BRSU). From 2006 to 2008, she contributed to the EU-funded project XPERO. Her thesis received the Best Thesis in Computer Science award for 2008 from BRSU. She is currently a PhD candidate at Osnabrück University and a Research Associate at BRSU. Her work is supported by a scholarship from their Graduate Institute. Her areas of research are in AI and robotics, with a focus on plan-based robot control, knowledge representation and reasoning, automated task planning, affordance-based robotics and robot control architectures.
Bonn-Rhein Sieg University of Applied Science
©2015 Walter de Gruyter Berlin/Boston
