System Safety Modeling of Alternative Geofencing Configurations for small UAS

Luxhøj, James T.

doi:10.15394/ijaaa.2016.1105

Cited by 7 publications

(2 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…When flying in close proximity to a structure it is not possible to rely on Global Navigation Satellite System (GNSS) for positioning due to its limited accuracy and susceptibility to occlusion and multipath errors [10]. Additionally, it is unlikely the vehicle will posses a high fidelity geofence [11] (corresponding to the physical outline of the structure) required for a GNSS system to assure adequate separation. Pilots must instead position the vehicle manually using an attitude stabilisation mode [12], requiring significant skill.…”

Section: Scenariomentioning

confidence: 99%

A model based design framework for safety verification of a semi-autonomous inspection drone

McAree

Aitken

Veres

2016

2016 UKACC 11th International Conference on Control (CONTROL)

View full text Add to dashboard Cite

Abstract-In this paper, we present a model based design approach to the development of a semi-autonomous control system for an inspection drone. The system is tasked with maintaining a set distance from the target being inspected and a constant relative pose, allowing the operator to manoeuvre the drone around the target with ease. It is essential that the robustness of the autonomous behaviour be thoroughly verified prior to actual implementation, as this will involve the flight of a large multi-rotor drone in close proximity to a solid structure. By utilising the Robotic Operating System to communicate between the autonomous controller and the drone, the same Simulink model can be used for numerical coverage testing, high fidelity simulation, offboard execution and final executable deployment.

show abstract

Section: Scenariomentioning

confidence: 99%

A model based design framework for safety verification of a semi-autonomous inspection drone

McAree

Aitken

Veres

2016

2016 UKACC 11th International Conference on Control (CONTROL)

View full text Add to dashboard Cite

show abstract

“…If the multicopter loses a navigation (e.g., GPS) signal or detects a critically low battery level, the multicopter will typically initiate an automatic landing protocol. 2 Electronic geofencing has also been proposed to prevent fly-away, 3,4 but to-date has relied on user entry or a sparse database of restricted sites, e.g., the White House lawn. This paper proposes a set of map-based fail-safe protocols that enable a multicopter experiencing an anomaly requiring a near-term landing, e.g., low battery energy, to safely terminate its flight in an urban environment where an immediate fail-safe landing poses risk to people on the ground.…”

Section: Introductionmentioning

confidence: 99%

Fail-Safe Navigation for Autonomous Urban Multicopter Flight

Ochoa

Atkins

2017

AIAA Information Systems-Aiaa Infotech @ Aerospace

View full text Add to dashboard Cite

Current multicopter fail-safe protocols respond with pre-programmed behaviors that aim to minimize possible damage to the aircraft or avoid risk to the nearby population. Existing fail-safe protocols for multicopters involve either returning to a pre-designated home point or executing an automatic landing protocol. Such strategies are rigid and can even increase risk in cases with complex terrain or high overflown population densities. This paper examines three alternative fail-safe protocols for autonomous urban multicopter flight that trade the simplicity of existing protocols with responsiveness to terrain, multicopter state, and overflown population. We utilize nontraditional data and sensor fusion to make an informed landing site selection with a focus on building rooftops as safe urban landing sites. The first protocol assigns a "Clearance to Land" flag to all buildings to determine the nearest rooftop in the area that can serve as a feasible landing site. The second protocol first determines a possible landing site within the multicopter's reachable footprint using lot types provided by a property database. During traversal to that site the multicopter examines the rooftops of overflown buildings and generates an alternative landing plan if it discovers a viable rooftop not previously mapped. The third protocol utilizes the known building locations and their approximate geometries as specified by the database to generate a spanning tree coverage solution followed by the multicopter to search for a viable landing site. A feature-based map of Manhattan generated from the PLUTO and MapPLUTO tax lot databases is used for simulations of all three protocols.

show abstract

Annotated Bibliography on the Impact of Geofencing as a Security Strategy Model

Ijeh¹

2018

Handbook of Cyber-Development, Cyber-Democracy, and Cyber-Defense

View full text Add to dashboard Cite

System Safety Modeling of Alternative Geofencing Configurations for small UAS

Cited by 7 publications

References 27 publications

A model based design framework for safety verification of a semi-autonomous inspection drone

A model based design framework for safety verification of a semi-autonomous inspection drone

Fail-Safe Navigation for Autonomous Urban Multicopter Flight

Annotated Bibliography on the Impact of Geofencing as a Security Strategy Model

Contact Info

Product

Resources

About