Gordon Keller | Search NASA

NASA NTRSDate not supplied

Enhanced UAS Availability via Vehicle to Vehicle Routing Scaled Experiments

The safe integration of modern unmanned aerial systems into the national airspace requires the ability to be able to confirm that the vehicles are working as planned. This means the availability of the vehicle and latency of the communication is critical. These requirements, along with a complex and multifaceted environment as well as the unmanned air traffic management framework, present a unique optimization problem. In this paper, we articulate our envisioned problem space and create a scaled-down version to test the functional feasibility of utilizing the vehicle to vehicle communication as a secondary communication assurance mechanism. We present our framework, experimental approach, and some lessons learned through the process.

Nicholas B Cramer↗

NASA NTRSDate not supplied

Adaptive Multi-Sensor Fusion Based Object Tracking for Autonomous Urban Air Mobility Operations

Autonomous operations are a crucial aspect in the context of Urban Air Mobility and other emerging aviation markets. In order to enable this autonomy, systems must be able to build independently an accurate and detailed understanding of the own vehicle state as well as the surrounding environment, this includes detecting and avoiding moving objects in the sky, which can be cooperative (aircraft, UAM vehicles, etc.) as well as noncooperative (smaller drones, birds, ...). This paper focuses on the object tracking part that relies on adaptive multi-sensor fusion, taking into account specific properties and limitations of different sensor types. Results show the impact of dropouts of individual sensors on the accuracy of the tracking results for this adaptive sensor fusion approach.

sensor fusion↗

NASA NTRSDate not supplied

Adaptive Multi-Sensor Fusion Based Object Tracking for Autonomous Urban Air Mobility Operations

Autonomous operations are a crucial aspect in the context of Urban Air Mobility and other emerging aviation markets. In order to enable this autonomy, systems must be able to build independently an accurate and detailed understanding of the own vehicle state as well as the surrounding environment, this includes detecting and avoiding moving objects in the sky, which can be cooperative (aircraft, UAM vehicles, etc.) as well as noncooperative (smaller drones, birds, ...). This paper focuses on the object tracking part that relies on adaptive multi-sensor fusion, taking into account specific properties and limitations of different sensor types. Results show the impact of dropouts of individual sensors on the accuracy of the tracking results for this adaptive sensor fusion approach.

object tracking↗