  Unmanned aircraft systems (UAS) are being increasingly adopted for various
applications. The risk UAS poses to people and property must be kept to
acceptable levels. This paper proposes risk-aware contingency management
autonomy to prevent an accident in the event of component malfunction,
specifically propulsion unit failure and/or battery degradation. The proposed
autonomy is modeled as a Markov Decision Process (MDP) whose solution is a
contingency management policy that appropriately executes emergency landing,
flight termination or continuation of planned flight actions. Motivated by the
potential for errors in fault/failure indicators, partial observability of the
MDP state space is investigated. The performance of optimal policies is
analyzed over varying observability conditions in a high-fidelity simulator.
Results indicate that both partially observable MDP (POMDP) and maximum a
posteriori MDP policies performed similarly over different state observability
criteria, given the nearly deterministic state transition model.
