No quantitative procedure currently exists to evaluate the obstacle avoidance capabilities of robotic applications. Such an evaluation method is needed for comparing different methods, but also to determine the operational limits of autonomous systems. This work proposes an evaluation framework which can find such limits. The framework comprises two sets of tests: detection tests and avoidance tests. For each set, environment and performance metrics need to be defined. For detection tests such metrics are well known. For avoidance tests however such metrics are not readily available. Therefore a new set of metrics is proposed. The framework is applied to a UAV that uses stereo vision to detect obstacles and three different algorithms to calculate the avoidance manoeuvre.