Fault tolerance is of increasing importance for modern autonomous industrial robots. The ability to detect and tolerate failures will enable robots to effectively cope with internal failures and continue performing assigned tasks without the need for immediate human intervention. To monitor fault tolerance actions performed by lower level routines and to provide higher level information about a robot's recovery capabilities, we use an expert system to develop a novel fault tolerance framework combining fault detection and tolerance routines with dynamic fault tree analysis. Fault tree analysis reveals the key components for providing fault detection and tolerance within a system. The trees can also be used quantitatively to provide a dynamic estimate of the probability of failure of the entire system or various subsystems. Using fault trees as a standard framework, the expert system package can provide fault tolerance for robots of significantly different origin and structure.