A Dynamic Navigation Model for Unmanned Aircraft Systems and an Application to Autonomous Front-On Environmental Sensing and Photography Using Low-Cost Sensor Systems

Sensors

Andrew James Cooper¹  Chelsea Anne Redman¹  David Mark Stoneham¹  Luis Felipe Gonzalez¹  Victor Kwesi Etse¹ 

关键词: unmanned aircraft system;    predictive path planning;    societal integration;    dynamic waypoint navigation;    aerial photography;    aerial filming;   

DOI  :  10.3390/s150921537

来源: mdpi

【 摘 要 】

This paper presents an unmanned aircraft system (UAS) that uses a probabilistic model for autonomous front-on environmental sensing or photography of a target. The system is based on low-cost and readily-available sensor systems in dynamic environments and with the general intent of improving the capabilities of dynamic waypoint-based navigation systems for a low-cost UAS. The behavioural dynamics of target movement for the design of a Kalman filter and Markov model-based prediction algorithm are included. Geometrical concepts and the Haversine formula are applied to the maximum likelihood case in order to make a prediction regarding a future state of a target, thus delivering a new waypoint for autonomous navigation. The results of the application to aerial filming with low-cost UAS are presented, achieving the desired goal of maintained front-on perspective without significant constraint to the route or pace of target movement.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.