Assessment of alternative manual control methods for small unmanned aerial vehicles

Author:

Stevenson Jonathan D.11,O'Young Siu11,Rolland Luc11

Affiliation:

1. Memorial University, St. John's, NL

Abstract

This paper is a summary of experiments to assess alternative methods to control a small (<25 kg; under Transport Canada rules, small UAV are classified as under 25 kg; Transport Canada. 2014. TP15263 – Knowledge requirements for pilots of unmanned air vehicle systems (UAV) 25 kg or less, operating within visual line of sight. Transport Canada. August. Available from http://www.tc.gc.ca/eng/civilaviation/publications/page-6557.html [accessed 17 August 2015]) unmanned aerial vehicle (UAV) in manual mode. While it is true that the majority of a typical UAV mission will be in automatic mode (i.e., using an autopilot) this may not always be the case during takeoffs and landings, or if there is a failure of the autopilot. The concept of a manual control backup mode during all flight phases remains in proposed UAV regulations currently being defined in Canada and the US. The research summarized in this paper is an attempt to assess the accuracy of several manual control options for a small UAV. The paper includes both a theoretical discussion of the task of manually controlling a small UAV airframe and results from a series of field experiments investigating the use of first-person view techniques.

Publisher

Canadian Science Publishing

Subject

Electrical and Electronic Engineering,Control and Optimization,Computer Science Applications,Aerospace Engineering,Automotive Engineering,Control and Systems Engineering

Reference12 articles.

1. Unmanned Aerial Vehicles: Autonomous Control Challenges, A Researcher's Perspective

2. Ellis, K. 2006. Investigation of emerging technologies and regulations for UAV ‘Sense and Avoid’ capability. National Research Council Institute for Aerospace Research, Report LTR-FR-258.

3. FAA. 2015. Operation and certification of small unmanned aircraft systems. FAA-2015-0150; Notice No. 15-01. Federal Aviation Administration, US Department of Transportation, Washington, DC.

4. Fat Shark. 2013. Attitude V2 FPV Goggle with trinity head tracking, User Manual, Revision B, 12/23/2013. Fat Shark RC Vision Systems.

5. Lerner, N.D. 1993. Brake perception-reaction times of older and younger drivers. Proceedings of the Human Factors and Ergonomics Society 37th annual meeting. Santa Monica, CA. pp. 206–210.

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