  We present an error tolerant path planning algorithm for Micro Aerial Vehicle
(MAV) swarms. We assume navigation without GPS-like techniques. The MAVs find
their path using sensors and cameras, identifying and following a series of
visual landmarks. The visual landmarks lead the MAVs towards their destination.
MAVs are assumed to be unaware of the terrain and locations of the landmarks.
They hold a priori information about landmarks, whose interpretation is prone
to errors. Errors are of two types, recognition or advice. Recognition errors
follow from misinterpretation of sensed data or a priori information, or
confusion of objects, e.g., due to faulty sensors. Advice errors are
consequences of outdated or wrong information about landmarks, e.g., due to
weather conditions. Our path planning algorithm is cooperative. MAVs
communicate and exchange information wirelessly, to minimize the number of
recognition and advice errors. Hence, the quality of the navigation decision
process is amplified. Our solution successfully achieves an adaptive error
tolerant navigation system. Quality amplification is parameterized with respect
to the number of MAVs. We validate our approach with theoretical proofs and
numeric simulations.
