Experiemntal platforms for evaluating sensor technology for UAS collision avoidance

Abstract

The problem of "sense-and-avoid" for Unmanned Aircraft Systems (UAS) is genuinely multi-dimensional: there is a wide range of UAS sizes, speeds, and maneuverability, as well as missions for which these UAS will be used. There are also a variety of sensors that might be used for sense-and-avoid, which have widely varying capabilities to measure distance or angle to an obstacle, as well as closing rate and time to collision. Most sensors are not able to provide all required information about the geometry of an encounter; therefore, using a combination of sensors offers one possible solution. We are investigating the concept that there may be a variety of possible sensor solutions for each distinct UAS capability or mission. By studying the breadth of UAS types and missions, and selectively testing certain sensors in the field, we are evaluating the limits to the capabilities of sensors and sensor combinations.This paper reports on part of the progress of this multi-dimensional evaluation. We have scoped the dimensions for evaluating UAS capabilities and the capabilities of sensors. We are experimentally evaluating sensor parameters on a variety of aircraft to validate the specified capabilities. This paper reports on our methodology for field evaluation of sensor technology and the lessons learned on evaluation platforms and capabilities.

Airborne vision‐based collision‐detection system

“…Machine vision represents a particularly attractive solution for sensing and detecting potential collision‐course targets due to the relatively low cost, size, weight, and power requirements of the sensors involved (Maroney, Boiling, Heffron, & Flathers, 2007). Man‐in‐the‐loop (MITL) solutions have been prototyped and demonstrated (Bryner, 2006).…”