Gershon Weltman

Measurement of trust in human-robot collaboration

We describe a collaborative performance model that captures the critical performance attributes of the distinctive human-robotic decision and control environment. The literature and our initial experimental studies show that the element of trust in human-robot collaboration is an extremely important factor in the performance model, and accordingly we have focused much of our attention on deriving suitable and practical measures of this variable. In this paper we describe the formulation of a decision-analytical based measure of trust as well as the results of two initial experiments designed to examine trust in a tactical human-robot collaborative task performed in our new mixed initiative team performance assessment system (MITPAS) simulation environment.

A Comprehensive Methodology for Assessing Human-Robot Team Performance for Use in Training and Simulation:

New methodologies and quantitative measurements for evaluating human-robot team performance must be developed to achieve effective coordination between teams of humans and unmanned vehicles. The Mixed Initiative Team Performance Assessment System (MITPAS) provides such a comprehensive measurement methodology. MITPAS consists of a methodology, tools and procedures to measure the performance of mixed manned and unmanned teams in both training and real world operational environments. This paper describes MITPAS and the results of an initial experiment conducted to validate the measures and gain insight into the effect of robot competence on operator trust as well as on human-robot team performance.

Police Department Personnel Stress Resilience Training: An Institutional Case Study

The objective of this case study was to test the impact in law enforcement personnel of an innovative self-regulation and resilience building program delivered via an iPad (Apple Inc, Cupertino, California) app and personal mentoring. The Stress Resilience Training System (SRTS) app includes training on stress and its effects, HRV coherence biofeedback, a series of HeartMath self-regulation techniques (The Institute of HeartMath, Boulder Creek, California), and HRV-controlled games. The stressful nature of law enforcement work is well established, and the need for meaningful and effective stress resilience training programs is becoming better understood, as it has been in the military. Law enforcement and military service share many stress-related features including psychological stressors connected with the mission, extended duty cycles, and exposure to horrific scenes of death and injury. San Diego (California) Police Department personnel who participated in the study were 12 sworn officers and 2 dispatchers, 10 men and 4 women. The SRTS intervention comprised an introductory 2-hour training session, 6 weeks of individualized learning and practice with the SRTS app, and four 1-hour telephone mentoring sessions by experienced HeartMath mentors spread over a four week period. Outcome measures were the Personal and Organizational Quality Assessment (POQA) survey, the mentors’ reports of their observations, and records of participants’ comments from the mentoring sessions. The POQA results were overwhelmingly positive: All four main scales showed improvement; Emotional Vitality improved by 25% (P=.05) and Physical Stress improved by 24% (P=.01). Eight of the nine subscales showed improvement, with the Stress subscale, perhaps the key measure of the study, improving by approximately 40% (P=.06). Participant responses were also uniformly positive and enthusiastic. Individual participants praised the program and related improvements in both on-the-job performance and personal and familial situations. The results support the efficacy of the program to achieve its goal of building stress resilience and improving officer wellness by providing practical self-regulation skills for better management of emotional energy. We conclude that the SRTS program for building resilience and improving psychological wellness can be as effective for law enforcement as it is for military personnel.

Designing an Adaptive Automation System for Human Supervision of Unmanned Vehicles: A Bridge from Theory to Practice:

Careful consideration must be given to the implementation of automation into complex systems. Much research in adaptive automation has identified challenges for system implementation. A key focus of this research has surrounded the methods of automation invocation including critical events, measurement, and modeling techniques. However, little consideration has been given to selecting and implementing appropriate techniques for a given system as a guide to designers of adaptive automation. This paper proposes such a methodology. We demonstrate the use of this methodology by describing a case study about a system designed to support effective communication and collaboration between the commander and vehicle operator in an unmanned aerial vehicle (UAV) system.

Multiagent Adjustable Autonomy Framework (MAAF) for multi-robot, multi-human teams

This paper describes the ongoing development of a multiagent adjustable autonomy framework (MAAF) for multi-robot, multi-human teams performing tactical maneuvers. The challenge being addressed in this SBIR Phase I R&D project is how to exploit fully the unique capabilities of heterogeneous teams composed of a mixture of robots, agents or persons (RAPs): that is, how to improve the safety, efficiency, reliability and cost of achieving mission goals while maintaining dynamic adaptation to the unique limitations and contingencies of a real-world operating environment. Our response to this challenge is the creation of a new infrastructure that will facilitate cooperative and collaborative performance of human and robots as equal team partners through the application of advances in goal-oriented, multiagent planning and coordination technology. At the heart of our approach is the USC Teamcore Groups Machinetta, a state-of-the-art robot proxy framework with adjustable autonomy. Machinetta facilitates robot-human role allocation decisions and collaborative sharing of team tasks in the non-deterministic and unpredictable military environment through the use of a domain-independent teamwork model that supports flexible teamwork. This paper presents our innovative proxy architecture and its constituent algorithms, and also describes our initial demonstration of technical feasibility in a realistic simulation scenario.

Size-distance invariance in perceptual adaptation

Objects viewed through a facemask under water appear larger and closer than when viewed in air. Divers’ adaptation to this distortion was measured by obtaining estimates of the size and distance of an array of targets before and after a 20-min underwater dive. A negative correlation between size- and distance-adaptation scores indicated that most divers adapted to one dimension by counteradapting to the other. For example, some Ss adapted to size by increasing the distortion of apparent distance and some the other way around. The results were discussed in relation to the size-distance invariance hypothesis.

Using Iterative Design and Testing Towards the Development of SRTS® A Mobile, Game-Based Stress Resilience Training System

The Stress Resilience Training System (SRTS®) is a new game-based learning application for tablets that trains users to better control stress through interactive education and advanced biofeedback. The goal of using the application is to allow users to better manage the positive and negative effects of stress. The application is targeted at young soldiers who may be more technologically- and game-motivated. An initial usability study with SRTS was conducted to determine its effectiveness and ease of use. A unique application of the link analysis method combined with retrospective probing revealed that users were following coach recommendations, but skipped vital information necessary to play the games. Results further showed that users with high subjective resilience were likely to find the application useful. Link analysis can help analyze exploratory learning behavior and relevant external comparison measures can inform future use of a product.

A Field-Theory Model of Blood-Pulse Measurement by Impedance Plethysmography

A field-theory model of blood-pulse measurement by four-electrode impedance plethysmography was developed and tested empirically. The model relates current distribution in the upper arm to the configuration of the drive electrodes. It predicts observed impedance change as a function of sense-electrode configuration and the increase in segmental volume associated with each blood pulse. The model was simulated on a digital computer for a number of critical cases. Corresponding measurements were taken on human subjects with an improved instrumentation system, which virtually eliminated the artifact caused by the skin-electrode interface. These measurements substantiated the major predictions of the model. It was concluded that precise impedance measurements were closely related to changes in segmental volume, and that any change in conductivity caused by the incoming arterial blood probably played a minor role. Insight was gained into the optimum placement of drive and sense electrodes at this measurement location.

TECRA: C2 application of adaptive automation theory

This paper describes the design and initial positive evaluation of a prototype adaptive automation system to create an enhanced command and control (C2) infrastructure for more effective operation of unmanned vehicles.1,2 Our main project objective is to apply recent advances in cognitive engineering and display automation to create Technology for Enhanced Command and Control of Small Robotic Assets (TECRA). The initial goal is an enhanced C2 system for small unmanned aircraft vehicles (SUAVs). Our approach is to use adaptive display technology to improve shared situation awareness between the SUAV Commander and the SUAV Operator, to provide new channels of Commander-Operator communication, and to reduce Commander workload.

A new Tactical Group Decision Analysis System (TGDAS) combining analytical and naturalistic decision modeling

The tactical group decision aiding system supports co-located or distributed teams who are planning missions requiring the selection of one among several possible options. Team members propose courses of action by creating scenarios, i.e., causally linked sequences of actions, key factors or events in the past, present, or future, and short or long-term mission outcomes. The TGDAS builds formally correct decision models via a scenario matrix that compares scenarios and identifies significant branch points, and by means of pre-stored editable templates that supply variables and relationships matching the scenario branch points in the relevant type of mission and situation. Model-based analyses order the options and let the collaborative team focus on variables that have the most impact on decisions and outcomes.