Health Monitoring of a Planetary Rover Using Hybrid Particle Petri Nets

Quentin Gaudel (1) , Pauline Ribot (1) , Elodie Chanthery (1) , Matthew J. Daigle (2)

1 LAAS-DISCO - Équipe DIagnostic, Supervision et COnduite
2 ARC - NASA Ames Research Center

This paper focuses on the application of a Petri Net-based diagnosis method on a planetary rover prototype. The diagnosis is performed by using a model-based method in the context of health management of hybrid systems. In system health management, the diagnosis task aims at determining the current health state of a system and the fault occurrences that lead to this state. The Hybrid Particle Petri Nets (HPPN) formalism is used to model hybrid systems behavior and degradation, and to define the generation of diagnosers to monitor the health states of such systems under uncertainty. At any time, the HPPN-based diagnoser provides the current diagnosis represented by a distribution of beliefs over the health states. The health monitoring methodology is demonstrated on the K11 rover. A hybrid model of the K11 is proposed and experimental results show that the approach is robust to real system data and constraints.

Mots clés: Diagnosis; Hybrid systems; Model-based monitoring; Health management; Uncertainty; Petri Nets; Particle filter

Domaines: Systèmes et contrôle [cs.SY]; Automatique / Robotique

Quentin Gaudel, Pauline Ribot, Elodie Chanthery, Matthew J. Daigle. Health Monitoring of a Planetary Rover Using Hybrid Particle Petri Nets. International Conference on Applications and Theory of Petri Nets and Concurrency, Jun 2016, Toruń, Poland. pp.196--215, ⟨10.1007/978-3-319-39086-4_13⟩. ⟨hal-01352011⟩