Fault Diagnosis and Accommodation in Quadrotor Simultaneous Localization and Mapping Systems

Anthony J. Green, Wright State University


Simultaneous Localization and Mapping (SLAM) is the process of using distance measurements to points in the surrounding environment to build a digital map and perform localization. It has been observed that featureless environments like tunnels or straight hallways will cause positioning faults in SLAM. This research investigates the fault diagnosis and accommodation problem for a laser-rangefinder-based SLAM systems on a quadrotor. A potential solution of using optical flow as velocity estimate and an extended Kalman filter (EKF) to perform position estimation is proposed. A fault diagnosis method for detecting faults in positional SLAM data or optical flow velocity data is developed by using two parallel EKFs. When a fault in the SLAM position or optical flow velocity is detected, the EKF adapts to provide a robust position estimate to ensure the safety of the flight control system.