An integrated model-based diagnosis and repair architecture for ROS-based robot systems

Autonomous robots are artifacts that comprise a significant number of heterogeneous hardware and software components and interact with dynamic environments. Therefore, there is always a chance of faults at run-time that negatively affect the reliability of the system. In this paper we present a novel diagnosis and repair architecture for ROS-based robot systems. It is an extension to the existing ROS diagnostics stack and follows a model-based diagnosis and repair approach. In the paper we discuss the integrated diagnosis and repair architecture in detail. Moreover, we show its application to an example robot system and report first experimental results. The presented work provides three major contributions: a combination of diagnosis and repair, the integration of hardware and software, and the integration into ROS.

[1]  Franz Wotawa,et al.  Real-Time Diagnosis and Repair of Faults of Robot Control Software , 2005, RoboCup.

[2]  Martin Heckmann,et al.  Learning a probabilistic self-awareness model for robotic systems , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[3]  Franz Wotawa,et al.  Towards Automated Online Diagnosis of Robot Navigation Software , 2008, SIMPAR.

[4]  Stefan Kohlbrecher,et al.  A flexible and scalable SLAM system with full 3D motion estimation , 2011, 2011 IEEE International Symposium on Safety, Security, and Rescue Robotics.

[5]  Feng Zhao,et al.  Distributed Monitoring of Hybrid Systems: A model-directed approach , 2001, IJCAI.

[6]  Raymond Reiter,et al.  A Theory of Diagnosis from First Principles , 1986, Artif. Intell..

[7]  Franz Wotawa,et al.  Model-Based Diagnosis or Reasoning from First Principles , 2003, IEEE Intell. Syst..

[8]  P. Pandurang Nayak,et al.  Remote Agent: To Boldly Go Where No AI System Has Gone Before , 1998, Artif. Intell..

[9]  Avrim Blum,et al.  Fast Planning Through Planning Graph Analysis , 1995, IJCAI.

[10]  Rachid Alami,et al.  An Architecture for Autonomy , 1998, Int. J. Robotics Res..

[11]  Feng Zhao,et al.  Fault modeling for monitoring and diagnosis of sensor-rich hybrid systems , 2001, Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228).

[12]  Franz Wotawa,et al.  Model-based fault diagnosis and reconfiguration of robot drives , 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[13]  Morgan Quigley,et al.  ROS: an open-source Robot Operating System , 2009, ICRA 2009.

[14]  Craig A. Knoblock,et al.  PDDL-the planning domain definition language , 1998 .