Machina Cognita Technologies (MCT) proposes the Autonomous Vehicle Audio Translation for Airfield Readiness (AVATAR) system for facilitating communications between airfield control authorities and Foreign Object Debris (FOD) removal vehicles. The system will provide a full conversational loop consisting of human-to-machine statement translation and a corresponding machine-to-human message- generation system. AVATAR will monitor continuous airfield radio signals and identify discrete speech segments despite challenges typical of airfield communications, including overlapping speakers, a variety of accents, and background noise. We will parse, classify, and filter the statements, relaying only those containing Air Traffic Control (ATC) instructions and questions for the relevant FOD-removal vehicles. When responding to ATC or negotiating permission for airfield navigation, the FOD-removal vehicle will have the ability to speak through AVATARs statement-generation module. Machine-generated messages will follow all airfield rules and regulations. Statements will be optimized for succinctness and directness to ensure a safe operating environment. The streamlined system will allow ATC to communicate with FOD-removal vehicles without unnecessary delay. In contrast to popular dialogue systems, AVATAR will maintain informational accuracy across conversations. The system will create a repository of situational information, including representations of ongoing movements of other airfield entities, histories of previous ATC statements, and details from daily operations plans. Relevant context from the repository will bolster the human-machine communication loop so that every ATC statement is understood accurately and every FOD-generated message is unambiguous. The system will incorporate geographic coordinates to provide spatial context for each translated statement and assist the FOD robot in averting potential collisions and airfield hazards. Each component of AVATAR will support an open interface with system users to promote compatibility. The system will provide processed data in any format necessary to ensure efficient communication. AVATAR-enabled FOD removal will increase airfield readiness and provide a much safer environment for naval aviation operations.
Benefit: The Autonomous Vehicle Audio Translation for Airfield Readiness (AVATAR) system proposed by Machina Cognita Technologies (MCT) will contribute to the development of a human-machine communication product with a broad range of applications. On Naval airfields, the product will yield three primary benefits to Foreign Object Debris (FOD) removal efforts. First, the system will translate human speech transmitted over airfield radio frequencies into formats that FOD-removal vehicles can interpret. Second, it will transform machine-produced communications originating from the FOD robot into audible speech for broadcast over appropriate radio frequencies. Third, the system will collect observations of airfield operations into an optimized database for informing safe FOD-vehicle routing and movement decisions. In providing these benefits, the product will eliminate the need for human assistants to accompany FOD removal vehicles navigating the airfield, thereby reducing the burden on Naval personnel. Furthermore, the system will support efficient airfield communications by streamlining human-machine dialogues, avoiding unnecessary confusion and delay. The fully developed AVATAR system will enable an autonomous FOD disposal program improving safety and readiness at Naval airports. In building the AVATAR system, MCT will prioritize compatibility with a wide-ranging set of data formats through an open interface, allowing us to share AVATARs benefits easily with other users within the FOD system-of-systems. This focus on product versatility will make AVATAR well suited for facilitating human-machine communication in autonomous vehicles in other domains. With minimal adaptation, AVATAR could provide human-machine translations to assist the Federal Aviation Administration (FAA) in its oversight of FOD disposal programs at civilian airports. Additionally, the product could integrate with commercial unmanned air systems (UAS) to facilitate autonomous ground and air ATC communications for commercial use. In any situation where autonomous systems must fit seamlessly into existing airfield operations, AVATAR will offer a foundation from which to build a reliable solution.
Keywords: Airfield Safety, Airfield Safety, Human Machine Teaming, Autonomy, Deep Learning, foreign object detection, Natural Language Processing, Machine Learning
