Automated Fault Diagnosis for an Autonomous Underwater Vehicle

This paper reports our results in using a discrete fault diagnosis system Livingstone 2 (L2), onboard an autonomous underwater vehicle (AUV) Autosub 6000. Due to the difficulty of communicating between an AUV and its operators, AUVs can benefit particularly from increased autonomy, of which fault diagnosis is a part. However, they are also restricted in their power consumption. We show that a discrete diagnosis system can detect and identify a number of faults that would threaten the health of an AUV, while also being sufficiently lightweight computationally to be deployed onboard the vehicle. Since AUVs also often have their missions designed just before deployment in response to data from previous missions, a diagnosis system that monitors the software as well as the hardware of the system is also very useful. We show how a software diagnosis model can be built automatically that can be integrated with the hardware model to diagnose the complete system. We show empirically that on Autosub 6000 this allows us to diagnose real vehicle faults that could potentially lead to the loss of the vehicle.

[1]  E. A..  Simulation-Based Verification of Autonomous Controllers via Livingstone PathFinder , 2004 .

[2]  Brian C. Williams,et al.  Mode Estimation of Probabilistic Hybrid Systems , 2002, HSCC.

[3]  David M. Lane,et al.  An integrated diagnostic architecture for autonomous underwater vehicles , 2007, J. Field Robotics.

[4]  M. Furlong,et al.  Low-Altitude Terrain following and Collision Avoidance in a Flight-Class Autonomous Underwater Vehicle , 2010 .

[5]  Brian C. Williams,et al.  Diagnosing Multiple Faults , 1987, Artif. Intell..

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

[7]  P. Pandurang Nayak,et al.  Back to the Future for Consistency-Based Trajectory Tracking , 2000, AAAI/IAAI.

[8]  P. Pandurang Nayak,et al.  A Model-Based Approach to Reactive Self-Configuring Systems , 1996, AAAI/IAAI, Vol. 2.

[9]  Nando de Freitas,et al.  Diagnosis by a waiter and a Mars explorer , 2004, Proceedings of the IEEE.

[10]  G. Griffiths,et al.  Predicting risk in missions under sea ice with Autonomous Underwater Vehicles , 2008, 2008 IEEE/OES Autonomous Underwater Vehicles.

[11]  Richard Dearden,et al.  Towards Diagnosis Modulo Theories , 2011 .

[12]  Adam Sweet,et al.  Lessons Learned in the Livingstone 2 on Earth Observing One Flight Experiment , 2005 .

[13]  Michel Kinnaert,et al.  Diagnosis and Fault-Tolerant Control , 2004, IEEE Transactions on Automatic Control.

[14]  Gianluca Antonelli.  Fault Detection/Tolerance Strategies for AUVs and ROVs , 2014 .

[15]  Richard Dearden,et al.  Particle Filters for Real-Time Fault Detection in Planetary Rovers , 2001 .

[16]  S. Narasimhan,et al.  HyDE – A General Framework for Stochastic and Hybrid Model-based Diagnosis , 2007 .

[17]  Angelo Alessandri,et al.  Robust Model-Based Fault Diagnosis for Unmanned Underwater Vehicles Using Sliding Mode-Observers , 1999 .

[18]  Brian C. Williams,et al.  Conflict-directed A* and its role in model-based embedded systems , 2007, Discret. Appl. Math..

[19]  Anna Philippou,et al.  Tools and Algorithms for the Construction and Analysis of Systems , 2018, Lecture Notes in Computer Science.

[20]  Nikolaj Bjørner,et al.  Symbolic Bounded Model Checking of Abstract State Machines , 2009, Int. J. Softw. Informatics.

[21]  Nicholas Kenelm Taylor,et al.  An integrated diagnostic architecture for autonomous underwater vehicles: Research Articles , 2007 .

[22]  Adam Sweet,et al.  Advanced Diagnostic System on Earth Observing One , 2004 .

[23]  M. Pebody.  The Contribution of Scripted Command Sequences and Low Level Control Behaviours to Autonomous Underwater Vehicle Control Systems and Their Impact on Reliability and Mission Success , 2007, OCEANS 2007 - Europe.

[24]  Aleksandar Feldman,et al.  Approximation Algorithms for Model-Based Diagnosis , 2010 .

[25]  Stephen D. McPhail,et al.  Autosub6000: A Deep Diving Long Range AUV , 2009 .

[26]  M. Pebody,et al.  Navigation and Control of an Autonomous Underwater Vehicle using a Distributed , 1998 .

[27]  Alessio Lomuscio,et al.  Verifying Fault Tolerance and Self-Diagnosability of an Autonomous Underwater Vehicle , 2011, IJCAI.