Honeywell Laboratories Research Articles

Contributors

Contributors

Prototype personal navigation system

Honeywell Laboratories recently funded the development of a prototype personal navigation system based on MEMS technologies. The system components include a MEMS inertial measurement unit, a three-axis magnetometer, a barometric pressure sensor, and a SAASM GPS receiver. The system also uses Honeywell's human motion-based pedometry algorithm. The navigation process is based on a strap-down inertial navigator aided by feedback from a Kalman filter using typical measurements from the GPS, magnetometer and barometer when available. A key innovation is the addition of an independent measurement of distance traveled based on the use of a human motion algorithm. The navigation system combines the best features of dead reckoning and inertial navigation, resulting in positioning performance exceeding that achieved with either method alone. Subsequent to the Honeywell effort, DARPA funded an individual Personal Inertial Navigation System (iPINS) seedling program. Honeywell worked to improve the baseline personal navigation system with the objective of demonstrating the feasibility of reliably achieving navigation accuracy < 1 % of distance traveled in GPS-denied scenarios. In addition, an analysis was conducted to determine the benefit of incorporating terrain correlation into the personal navigation system. The results of this analysis indicate that overall navigation accuracy can be significantly improved through the application of terrain correlation. This presents an are presented. In addition, conclusions from the terrain correlation analysis conducted under the iPINS seedling program are included.

Decentralized Receding Horizon Control and Coordination of Autonomous Vehicle Formations

This paper describes the application of a novel methodology for high-level control and coordination of autonomous vehicle teams and its demonstration on high-fidelity models of the organic air vehicle developed at Honeywell Laboratories. The scheme employs decentralized receding horizon controllers that reside on each vehicle to achieve coordination among team members. An appropriate graph structure describes the underlying communication topology between the vehicles. On each vehicle, information about neighbors is used to predict their behavior and plan conflict-free trajectories that maintain coordination and achieve team objectives. When feasibility of the decentralized control is lost, collision avoidance is ensured by invoking emergency maneuvers that are computed via invariant set theory.

Neuro-Physiologically-Driven Adaptive Automation to Improve Decision Making Under Stress

The advent of netted communications and a wide array of battlefield sensors is enabling real-time information streaming and asset management. However, the burden of information management is placed solely on the receiver of the information. Honeywell Laboratories developed a Communications Scheduler (CoS), an adaptive information management system for the dismounted Soldier, driven by an assessment of the individual's current cognitive capacity to process incoming information, in order to improve decision making under high task load conditions. An evaluation was conducted to demonstrate whether cognitive capacity to perform under differing task loads could be detected using neuro-physiological sensors and then if the adaptive automation would appropriately regulate information flow. Results revealed an improvement in primary task performance, no degradation in concurrent secondary tasks, and lower subjective workload ratings while performing cognitively challenging working memory tasks with the CoS, although a slight loss in situation awareness of lower priority message was found. The appropriate allocation of cognitive resources is key to managing multiple tasks, focusing on the most important ones, and maintaining overall situation awareness.

DETER: Detection of events for threat evaluation and recognition

The current security infrastructure can be summarized as follows: (1) Security systems act locally and do not cooperate in an effective manner, (2) Very valuable assets are protected inadequately by antiquated technology systems and (3) Security systems rely on intensive human concentration to detect and assess threats.In this paper we present DETER (Detection of Events for Threat Evaluation and Recognition), a research and development (R&D) project aimed to develop a high-end automated security system. DETER can be seen as an attempt to bridge the gap between current systems reporting isolated events and an automated cooperating network capable of inferring and reporting threats, a function currently being performed by humans.The prototype DETER system is installed at the parking lot of Honeywell Laboratories (HL) in Minneapolis. The computer vision module of DETER reliably tracks pedestrians and vehicles and reports their annotated trajectories to the threat assessment module for evaluation. DETER features a systematic optical and system design that sets it apart from "toy" surveillance systems. It employs a powerful Normal mixture model at the pixel level supported by an expectation-maximization (EM) initialization, the Jeffreys divergence measure, and the method of moments. It also features a practical and accurate multicamera calibration method. The threat assessment module utilizes the computer vision information and can provide alerts for behaviors as complicated as the "hopping" of potential vehicle thieves from vehicle spot to vehicle spot.Extensive experimental results measured during actual field operations support DETER's exceptional characteristics. DETER has recently been successfully productized. The product-grade version of DETER monitors movements across the length of a new oil pipeline.

Integrating Critical Information on Flight Deck Displays

Honeywell Laboratories has developed a concept for integrating multiple sources of data concerning information outside the aircraft. The concept, ANCOA (Alerting and Notification for Conditions Outside the Aircraft), was conceived as means for reducing error conflicts and establishing a clear prioritization among currently independent and disparate alerting systems for hazards external to the aircraft (e.g., TCAS, EGPWS). This paper documents an empirical evaluation of ANCOA by 12 professional pilots. The concept was evaluated in Honeywell Laboratories' Flight Simulation Laboratory in Minneapolis, Minnesota. Two core ANCOA features were manipulated and compared. The first was the integration of information by comparing ANCOA's integrated, overlaid features to a traditional display layout where the information was available on separate displays. The second variable was the categorization for incoming alerts (traffic, terrain, weather, scheduling constraints) by comparing alerts sorted by category to those without a category differentiation. Data support the integration of currently disparate systems onto a single display with performance requiring fewer pilot inputs and yielding lower workload scores. Categorization had little influence on pilot performance.