Task harmonisation for a single-task robot controller

The technical capabilities of robots and their increased versatility require a single robot to be able to perform a wide array of complex tasks. What more, when performing a task, it may be asked to carry out another one. Switching between different tasks is a known problem in engineering, however, robots, compared to programs operating in a virtual space, are unique as they must follow laws of physics. In this work, we introduce a method for harmonising service robot tasks being managed by finite state machines. The method allows for the handling of safe suspend and resume procedures for a complex task. Additionally, we consider a case when the robot can not switch the current task to another at any time. The method was implemented and verified by conducting multiple interruptions of one task by another one. The tasks during the verification were being performed in simulation by a TIAGo robot.

[1]  Matthias Scheutz,et al.  Architectural mechanisms for dynamic changes of behavior selection strategies in behavior-based systems , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[2]  Tomasz Winiarski,et al.  Cloud computing support for the multi-agent robot navigation system , 2017 .

[3]  Jingjing Huang,et al.  Development of An In-building Transport Robot for Autonomous Usage of Elevators , 2018, 2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR).

[4]  Tomasz Winiarski,et al.  Nao Robot Navigation System Structure Development in an Agent-Based Architecture of the RAPP Platform , 2016, AUTOMATION.

[5]  Raul Acuna,et al.  Development of a Control Platform for the Mobile Robot Roomba Using ROS and a Kinect Sensor , 2013, 2013 Latin American Robotics Symposium and Competition.

[6]  Jonathan Bohren,et al.  The SMACH High-Level Executive [ROS News] , 2010 .

[7]  Rachid Alami,et al.  Toward Human-Aware Robot Task Planning , 2006, AAAI Spring Symposium: To Boldly Go Where No Human-Robot Team Has Gone Before.

[8]  Cezary Zielinski,et al.  Agent-Based Structures of Robot Systems , 2017, KKA.

[9]  Maciej Stefanczyk,et al.  Control system design procedure of a mobile robot with various modes of locomotion , 2016, 2016 21st International Conference on Methods and Models in Automation and Robotics (MMAR).

[10]  Satyandra K. Gupta,et al.  Towards robust assembly with knowledge representation for the planning domain definition language (PDDL) , 2015 .

[11]  Krzysztof Tchon,et al.  Motion Planning for the Mobile Platform Rex , 2014, Recent Advances in Automation, Robotics and Measuring Techniques.

[12]  Geoffrey C. Fox,et al.  Effective real-time scheduling algorithm for cyber physical systems society , 2014, Future Gener. Comput. Syst..

[13]  Cezary Zielinski,et al.  Variable structure robot control systems: The RAPP approach , 2017, Robotics Auton. Syst..

[14]  Patrizia Beraldi,et al.  An adjustable robust optimization model for the resource-constrained project scheduling problem with uncertain activity durations , 2017 .

[15]  Gabriele Trovato,et al.  Robotman: A security robot for human-robot interaction , 2017, 2017 18th International Conference on Advanced Robotics (ICAR).

[16]  E. Gat.  On Three-Layer Architectures , 1997 .

[17]  Konrad Banachowicz,et al.  Multibehavioral position-force manipulator controller , 2016, 2016 21st International Conference on Methods and Models in Automation and Robotics (MMAR).

[18]  Konrad Banachowicz,et al.  Distributed NAO robot navigation system in the hazard detection application , 2016, 2016 21st International Conference on Methods and Models in Automation and Robotics (MMAR).