Unmanned Aerial System Operator Selection Tools
Navy SBIR FY2013.1


Sol No.: Navy SBIR FY2013.1
Topic No.: N131-082
Topic Title: Unmanned Aerial System Operator Selection Tools
Proposal No.: N131-082-0041
Firm: Perceptronics Solutions, Inc.
3527 Beverly Glen Blvd.
Sherman Oaks, California 91423
Contact: Gershorn Weltman
Phone: (818) 788-1025
Web Site: www.percsolutions.net
Abstract: This proposal is to develop new Operator Selection Tools for Unmanned Aerial Systems (UAS). Our goal is to enhance the effectiveness of UAS operator selection by adding to the conventional methodology of selection tests new measures for the new skills and aptitudes associated with the control of intelligent, semi-autonomous robotic systems. Taking this need into account, we have oriented our proposed SBIR project toward the critical aspects of future UAG operations that are inadequately covered in current selection systems. These concern the ability of the operator to work within the two required types of UAS teams, namely: (1) Mixed-Initiative Teams (the operator and single or multiple semi-autonomous UASs). The key mixed-initiative team skill factors will include supervisory control capability and accurate trust in automation; (2) Inter-Personal Teams (the operator, the commander, the mission controller, etc). The optimal formation and functioning of such inter-personal teams will be of critical importance to successful UAS operations. In other words, both near-term and long-term UAS operating requirements will change dramatically as UV technology evolves, and the UAS operator and crew courses will have to change accordingly. As a result, new selection criteria must be added to current criteria to accommodate these changes.
Benefits: Implementation of a properly constructed measurement-based process for UAS flight training that includes consideration of novel skills required by today's and tomorrow's increasingly autonomous UASs will reduce training losses, thereby reducing training costs, and will increase the overall effectiveness of UAS operation in both their military and non-military applications. The process itself (typically a test battery and statistically based decision criterion) must itself provide the basis for evaluation of its own effectiveness. Our newly constructed selection process will establish a rigorous KSAO list so that measures can be adapted or developed to assess the maximum range of relevant attributes that can be measured economically. We will analyze current UAS job analyses in Phase I to identify deficiencies and augment them fully with new selection criteria in the Phase II effort. Moreover, we will extend current UAS selection procedures by considering the UAS operator as a part of two types of team: mixed-initiative and inter-personal, and will explore the use of modeling technology for personnel classification and team formation based on the measures obtained from the selection tools. Finally, our prototype product will be immediately suitable for use by Navy and other military programs as well as by air carriers and other aviation services that typically have little information technology support and few personnel available to administer selection instruments.

Return