SAFEGUARD: Progress and test results for a reliable independent on-board safety net for UAS

As demands increase to use unmanned aircraft systems (UAS) for a broad spectrum of commercial applications, regulatory authorities are examining how to safely integrate them without compromising safety or disrupting traditional airspace operations. For small UAS, several operational rules have been established; e.g., do not operate beyond visual line-of-sight, do not fly within live miles of a commercial airport, do not fly above 400 ft above ground level. Enforcing these rules is challenging for UAS, as evidenced by the number of incident reports received by the Federal Aviation Administration (FAA). This paper reviews the development of an onboard system — Safeguard — designed to monitor and enforce conformance to a set of operational rules defined prior to flight (e.g., geospatial stay-out or stay-in regions, speed limits, and altitude constraints). Unlike typical geofencing or geo-limitation functions, Safeguard operates independently of the off-the-shelf UAS autopilot and is designed in a way that can be realized by a small set of verifiable functions to simplify compliance with existing standards for safety-critical systems (e.g. for spacecraft and manned commercial transportation aircraft systems). A framework is described that decouples the system from any other devices on the UAS as well as introduces complementary positioning source(s) for applications that require integrity and availability beyond what can be provided by the Global Positioning System (GPS). This paper summarizes the progress and test results for Safeguard research and development since presentation of the design concept at the 35th DASC (2016). Significant accomplishments include completion of software verification and validation in accordance with NASA standards for spacecraft systems (to Class B), development of improved hardware prototypes, development of a simulation platform that allows for hardware-in-the-loop testing and fast-time Monte Carlo evaluations, and flight testing on multiple air vehicles. Integration testing with NASA's UAS Traffic Management (UTM) service-oriented architecture was also demonstrated.

[1]  Hoyt Lougee,et al.  SOFTWARE CONSIDERATIONS IN AIRBORNE SYSTEMS AND EQUIPMENT CERTIFICATION , 2001 .

[2]  韓國航空大學 航空 械工學科 美聯邦航空廳(Federal Aviation Administration)의 航空機 製作檢査 制度의 現況 , 1979 .

[3]  Chris Rizos Locata: A Positioning System for Indoor and Outdoor Applications Where GNSS Does Not Work , 2013 .

[4]  Kelly J. Hayhurst,et al.  A case study for assured containment , 2015, 2015 International Conference on Unmanned Aircraft Systems (ICUAS).

[5]  Vps Naidu,et al.  Geo-Fencing for Unmanned Aerial Vehicle , 2015 .

[6]  Parimal H. Kopardekar Unmanned Aerial System (UAS) Traffic Management (UTM): Enabling Low-Altitude Airspace and UAS Operations , 2014 .

[7]  Ella M. Atkins,et al.  Multi-Mode Guidance for an Independent Multicopter Geofencing System , 2016 .

[8]  Pierre Marzin,et al.  Understanding Formal Methods , 2003, Springer London.

[9]  Kelly J. Hayhurst,et al.  SAFEGUARD: An assured safety net technology for UAS , 2016, 2016 IEEE/AIAA 35th Digital Avionics Systems Conference (DASC).

[10]  Ella M. Atkins Autonomy as an enabler of economically-viable, beyond-line-of-sight, low-altitude UAS applications with acceptable risk , 2014 .

[11]  Lui Sha,et al.  Simplex Architecture: Meeting the Challenges of Using COTS in High-Reliability Systems , 1998 .

[12]  R Berg,et al.  TITLE 14 CODE OF FEDERAL REGULATIONS PART 145 APPROVED TRAINING PROGRAM: RESEARCH AND RECOMMENDATIONS , 2004 .

[13]  Kelly J. Hayhurst,et al.  Design Requirements for Unmanned Rotorcraft Used in Low-Risk Concepts of Operation , 2016 .

[14]  Maria Consiglio,et al.  ICAROUS: Integrated configurable algorithms for reliable operations of unmanned systems , 2016, 2016 IEEE/AIAA 35th Digital Avionics Systems Conference (DASC).