Vanderbilt School of Engineering

Future emergency incident responses, including Chemical, Biological, Radiological, Nuclear, and Explosive (CBRNE), will incorporate robots. The ability to interact with robots and understand the resulting volumes of information requires a system of human-robot interfaces employing directable visualizations that provide information immediacy, relevancy, and sharing appropriate for each human’s responsibilities.
This dissertation conducted two modified Cognitive Tasks Analyses (CTA) on the CBRNE incident response. The Cognitive Information Flow Analysis (CIFA) was developed to combine CTA results and to analyze the path of information as it passes through and is transformed by the system at different human-robot interaction (HRI) user levels. These analyses (i.e., modified CTAs and CIFA) collectively informed the HRI design and development.

The primary contributions of this dissertation are the development and evaluation of two novel visualization techniques that present immediate, relevant, and shared information provided by the robots to the human users in the system of human-robot interfaces. The General Visualization Abstraction (GVA) algorithm, the first technique, is designed to provide information immediacy and relevancy by displaying the most useful information at any given moment determined by rewarding information that is either historically and currently relevant or novel and emerging. The Decision Information Abstracted to a Relevant Encapsulation (DIARE) concept, the second technique, supports decision-making by representing prior event information as a defined volume in the visualization’s information space and encapsulates the volume into an explicit and visual object that can be shared across time and users.

User evaluations were conducted for both visualization techniques. The GVA algorithm’s evaluation results indicate that it can reduce cognitive workload, increase situational awareness, and improve performance for two different HRI user levels. The DIARE concept results indicate that participants were able to rapidly ascertain what had happened previously with great accuracy and good memory recall. Together, these two visualization techniques can assist decision-makers using directable visualizations, such as those used in HRI, by offering an effective method of sharing and providing real-time, relevant information.

Related Papers:

Curtis M. Humphrey. Information Abstraction Visualization for Human-Robot Interaction. PhD thesis,Vanderbilt University, August 2009

Related posts:

1. Emergency Response System Human-Robot Interaction User Levels
2. General Visualization Abstraction Algorithm for Geographic Map-Based Directable Interfaces
3. Addressing Information Sharing in Directable Interfaces via DIARE Concept

Cognitive Infomation Flow Analysis for Emergency Evaluation

The Cognitive Information Flow Analysis (CIFA) is a method to combine results from multiple cognitive task analyses while providing a focus on the necessary system information flow, which includes how information is produced, consumed, and transformed by the various system functions and users. This project explored the CIFA concept, conducted a case study that applies the CIFA method to existing Goal-Direct Task Analysis and modified Cognitive Work Analysis results, and investigated CIFA’s use for informing the design of a system of human-robot interfaces.

CIFA can serve as a guide for system design and development. CIFA also provides a number of advantages over combining cognitive task analysis results using relational tables. First, CIFA can express the interconnectivity of the various system subcomponents, including partial ordering and parallelism, by fundamentally focusing on the information flow. Second, CIFA can identify both existing and potential, information bottlenecks and highlight teamwork.

Related Papers:

Humphrey, C. M., & Adams, J. A. (2009). Cognitive Information Flow Analysis: Definition and Case Study. Manuscript submitted for publication.

Related posts:

1. CBRNE Event Analysis
2. Ph.D. Thesis: Information Abstraction Visualization for Human-Robot Interaction
3. Robotic Tasks for CBRNE Incident Response