Nowadays, advances in sensor, actuator, and processing technologies have permitted to shrink rotorcraft down to a micro-scale. Thanks to their hovering capability and high maneuverability, micro rotorcraft, classified as micro aerial vehicles (MAVs), are well suited for operating within constrained indoor environments. The autonomous navigation of these vehicles in such environments is a challenge for two main reasons. First, due to payload and energy restrictions, a MAV is equipped with the least quantity of sensors. Second, operation within a constrained environment will place a MAV close to objects, which will induce aerodynamic interactions. The most studied aerodynamic interaction is the ground effect, which can be explained as the cushion of air under the vehicle when it flies closely over a rigid surface. In this thesis, we propose a novel approach for rejecting disturbances induced by the ground effect. To retrieve the position of the vehicle, we employ a monocular camera, which is a lightweight and energy-efficient sensor. Also, we provide experimental evidence that the ground effect induces sensor faults. For that reason, we develop the approach as a faulttolerant control scheme, which consists of a detection strategy and mitigation strategy. We assume a hierarchical control structure for trajectory tracking. Specifically, we assume that the nominal control structure consists of an external PD controller and an internal PI controller. In experimental tests, we found that the sensor faults occur on the inner loop, which we counteract in the outer loop by switching between control actions. In a novel approach, we use a metric monocular SLAM algorithm for detecting internal faults. We design the fault detection scheme as a logical process that depends on the weighted residual between inner and outer estimations. Furthermore, we propose two control strategies for fault mitigation. The first combines the external PD controller and a function of the residual (FTC 1). The second treats the sensor fault as an actuator fault and compensates with a sliding mode action (FTC 2). In either case, we utilize onboard sensors only. We evaluate the effectiveness of the strategies in simulations and experiments. The experimental results show that FTC 1 surpasses FTC 2. Finally, we explore the usage of optical flow estimations for the detection and mitigation of the ground effect.