Autonomous navigation of UAV in forest

This paper presents a navigation system that enables small-scale unmanned aerial vehicles to navigate autonomously in foliage environment without GPS using a 2D laser range finder. The navigation framework consists of real-time onboard motion estimation and trajectory smoothing using pose graph optimization, real-time dual layer control. In particular, onboard real-time motion estimation is achieved in a Kalman filter, fusing the planar velocity measurement from scan matching of laser range finder and the acceleration measurement of inertial measurement unit. The trajectory histories from the real-time autonomous navigation together with the observed features are fed into a pose-graph optimization framework. Poses in a sliding window are optimized using GraphSLAM technique. The inner loop of a quadrotor is stabilized using a commercial autopilot while the outer loop control is implemented using robust perfect tracking. The performance of the navigation system is demonstrated on the successful autonomous navigation of a small-scale UAV in forest. Consistent mapping of the environment in indoor and outdoor scenarios are achieved by projecting all the scan measurement on the post-optimized trajectory with GraphSLAM.