Vision Based Horizon Detection for UAV Navigation
ADVANCES IN SERVICE AND INDUSTRIAL ROBOTICS, RAAD 2018(2019)
摘要
In this paper, we present a novel framework for horizon line (HL) detection that can be effectively used for Unmanned Air Vehicle (UAV) navigation. Our scheme is based on a Canny edge and a Hough detector along with an optimization step performed by a Particle Swarm Optimization (PSO) algorithm. The PSO's objective function is based on a variation of the Bag of Words (BOW) method to effectively consider multiple image descriptors and facilitate efficient computation times. More specifically, the image descriptors employed are L * a * b color features, texture features, and SIFT features. We demonstrate the effectiveness and robustness of the proposed novel horizon line detector in multiple image sets captured under real world conditions. First, we experimentally compare the proposed scheme with the Hough HL detector and a deep learning HL estimator, a prominent example of line detection, and demonstrate a significant boost in accuracy. Furthermore, since from the horizon line the UAV roll and pitch angles can be derived, this scheme can be used for UAV navigation. To this end, to further validate our approach, we compare the horizon computed roll and pitch angles to the IMU ones obtained with a complementary filter.
更多查看译文
关键词
Horizon line detector,Unmanned air vehicle,Particle Swarm Optimization,Bag of Words,Pitch and roll angles derivation
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络