Richard Washington. On-board real-time state and fault identification for rovers. In Proceedings of the 2000 IEEE International Conference on Robotics and Automation, ICRA 2000, April 24-28, 2000, San Francisco, CA, USA, pages 1175--1181, 2000. Home/Search Document Details and Download
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Rao-Blackwellised Particle Filtering for Fault Diagnosis - de Freitas (2001) (6 citations) (Correct)
....FILTERING 5 EXPERIMENTS 6 CONCLUSIONS 7 ACKNOWLEDGMENTS 1. INTRODUCTION Automatic fault diagnosis is a fundamental problem in aerospace systems and autonomous robotics. Planetary rovers, for example, must be able to diagnose faults and carry out repairs without ground operator intervention [18]. In a typical diagnosis scenario, the machine (e.g. electronic system or robot) receives a continuous stream of data from various on board sensors. It, subsequently, processes this information to identify its discrete state of operation (e.g. stuck rear wheel , normal operation , damaged ....
....and continuous states and the statistical properties of the data. Typically, the continuous states and measurements are assumed to be Gaussian distributed. One problem with the required models is that they are intractable. This has motivated the development of algorithms for approximate inference [18], 17] The state ofthe art method is the Monte Carlo particle filter proposed in [17] This method allows one to compute, recursively in time, a stochastic point mass approximation of the posterior distribution of the states given the observations. For a comprehensive review of Monte Carlo ....
R Washington. On-board real-time state and fault identification for rovers. In IEEE International Conference on Robotics and Automation, 2000.
Particle Filters for Real-Time Fault Detection in Planetary.. - Dearden, Clancy (2002) (8 citations) (Correct)
....As we said above, we model a rover as a hybrid system. The discrete component of the rover s state represents the various operational and fault modes of the rover, while the continuous state describes the speed of the wheels, the current being drawn by various subsystems, and so on. Following [13], our rover model consists of a tuple 9999 99 where the elements of the tuple are as follows: is the set of discrete modes the system can be in. We assume that is finite, and write for an individual system mode. is the set of variables describing the continuous state of ....
....has a number of sensors, but we will restrict our attention to diagnosing the state of the broken wheel, and will therefore use only data from the wheel current and wheel odometry sensors. We will treat each wheel independently in the diagnosis. For each wheel, we have a model, taken from [13], with the following characteristics: consists of .0 system modes of which 1 2 are fault states. consists of variables for the wheel current and wheel speed, and the derivatives of current and speed. is a fairly sparse matrix, with at most six successors for any given mode. The ....
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Rich Washington, `On-board real-time state and fault identification for rovers', in Proceedings of the IEEE International Conference on Robotics and Automation, (April 2000).
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Richard Washington. On-board real-time state and fault identification for rovers. In Proceedings of the 2000 IEEE International Conference on Robotics and Automation, ICRA 2000, April 24-28, 2000, San Francisco, CA, USA, pages 1175--1181, 2000.
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R. Washington, On-Board Real-Time State and Fault Identification for Rovers, 2000.
Efficient Failure Detection for Mobile Robots Using.. - Plagemann, Stachniss, .. (2006) (Correct)
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R. Washington. On-board real-time state and fault identification for rovers. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages 1175--1181, 2000.
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R. Washington, "On-board real-time state and fault identification for rovers," in IEEE International Conference on Robotics and Automation, 2000.
Diagnosis by a Waiter and a Mars Explorer - Nando De Freitas (2003) (5 citations) (Correct)
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R. Washington, "On-board real-time state and fault identification for rovers," in IEEE International Conference on Robotics and Automation, 2000.
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