A Survey and Categorization of Small Low-Cost Unmanned Aerial Vehicle System Identification

Remote sensing has traditionally be done with satellites and manned aircraft. While these methods can yield useful scientific data, satellites and manned aircraft have limitations in data frequency, process time, and real time retasking. Small low-cost unmanned aerial vehicles (UAVs) can bridge the gap for personal remote sensing for scientific data. Precision aerial imagery and sensor data requires an accurate dynamics model of the vehicle for controller development. One method of developing a dynamics model is system identification (system ID). The purpose of this paper is to provide a survey and categorization of current methods and applications N. V. Hoffer (B) · C. Coopmans Center for Self-Organizing and Intelligent Systems (CSOIS), Utah State University, Logan, UT, USA e-mail: [email protected] C. Coopmans e-mail: [email protected] A. M. Jensen AggieAir Flying Circus (AAFC), Utah Water Research Laboratory, Utah State University, Logan, UT, USA e-mail: [email protected] Y. Q. Chen Mechatronics, Embedded Systems and Automation (MESA) Lab, University of California, Merced, Merced, CA, USA e-mail: [email protected] of system ID for small low-cost UAVs. This paper also provides background information on the process of system ID with in-depth discussion on practical implementation for UAVs. This survey divides the summaries of system ID research into five UAV groups: helicopter, fixed-wing, multirotor, flapping-wing, and lighter-than-air. The research literature is tabulated into five corresponding UAV groups for further research.