The effects of uncertainty on plan success in a simulated maintenance robot domain

Autonomous robots must be designed to function in real-world domains. These domains are characterized by uncertainty, yet little work has been done to quantify the effects of uncertainty on goal satisfaction. Our research on simulated repair robots indicates that different types of uncertainty have fundamentally different relationships to plan success. This paper investigates the impacts of sensor inaccuracies, exogenous events and failures in both motion and gripper operations. Extensive simulations provide the basis for mathematical models of the relationship between these types of uncertainties and plan success. In addition, the impact of current heuristics such as ‘retry on failure’, and ‘tell me three times’ is investigated. Concluding that even low levels of uncertainty can significantly impact goal satisfaction in a stimulated repair robot domain and that repeated attempts provide significant improvement in plan success rates in the face of uncertainty.