6 accepted papers
We propose a planning method to enable fast autonomous flight in cluttered environments. Typically, autonomous navigation through a complex environment requires a continuous search on a graph generated by a k-connected grid or a probabilistic scheme. As the vehicle travels, updating the graph with d…
We propose a novel method to enable fast autonomous flight in cluttered environments. Typically, autonomous navigation through a complex environment requires a continuous heuristic search on a graph generated by a k-connected grid or a probabilistic scheme. As the vehicle progresses, modification of…
We present a data processing pipeline to online estimate ego-motion and build a map of the traversed environment, leveraging data from a 3D laser, a camera, and an IMU. Different from traditional methods that use a Kalman filter or factor-graph optimization, the proposed method employs a sequential,…
Despite significant progress in GPS-denied autonomous flight, long-distance traversals (> 100 km) in the absence of GPS remain elusive. This paper demonstrates a method capable of accurately estimating the aircraft state over a 218 km flight with a final position error of 27 m, 0.012% of the distanc…
Positioning and mapping can be conducted accurately by state-of-the-art state estimation methods. However, reliability of these methods is largely based on avoiding degeneracy that can arise from cases such as scarcity of texture features for vision sensors and lack of geometrical structures for ran
Here, we present a general framework for combining visual odometry and lidar odometry in a fundamental and first principle method. The method shows improvements in performance over the state of the art, particularly in robustness to aggressive motion and temporary lack of visual features. The propos…