Magician simulator — A realistic simulator for heterogeneous teams of autonomous robots

We report on the development of a new simulation environment for use in Multi-Robot Learning, Swarm Robotics, Robot Teaming, Human Factors and Operator Training. The simulator provides a realistic environment for examining methods for localization and navigation, sensor analysis, object identification and tracking, as well as strategy development, interface refinement and operator training (based on various degrees of heterogeneity, robot teaming, and connectivity). The simulation additionally incorporates real-time human-robot interaction and allows hybrid operation with a mix of simulated and real robots and sensor inputs

ErgoShip 2021 – Maritime artikler

Welcome to the special issue dedicated to the conference Ergoship 2021! The editorial committee are proud to present a selection of papers from Ergoship 2021 and a few invited papers within the topic of maritime Human Factors. The first Ergoshipwas held in Gothenburg in 2011 to create a meeting place for researchers in maritime Human Factors. The conference has lived on and was held in Australia 2016, in Haugesund 2019 and in South Korea 2021. We wish we could all have met in person, but this time it was not to be. Nevertheless, we look forward to sharing these papers with you and hope we can drive this field forward together. Enjoy the papers from a small but passionate group of contributors. The authors and the audience make this recurring conference special

An Evaluation Schema for the Ethical Use of Autonomous Robotic Systems in Security Applications

We propose a multi-step evaluation schema designed to help procurement agencies and others to examine the ethical dimensions of autonomous systems to be applied in the security sector, including autonomous weapons systems

Evidence Report, Risk of Inadequate Design of Human and Automation/Robotic Integration

The success of future exploration missions depends, even more than today, on effective integration of humans and technology (automation and robotics). This will not emerge by chance, but by design. Both crew and ground personnel will need to do more demanding tasks in more difficult conditions, amplifying the costs of poor design and the benefits of good design. This report has looked at the importance of good design and the risks from poor design from several perspectives: 1) If the relevant functions needed for a mission are not identified, then designs of technology and its use by humans are unlikely to be effective: critical functions will be missing and irrelevant functions will mislead or drain attention. 2) If functions are not distributed effectively among the (multiple) participating humans and automation/robotic systems, later design choices can do little to repair this: additional unnecessary coordination work may be introduced, workload may be redistributed to create problems, limited human attentional resources may be wasted, and the capabilities of both humans and technology underused. 3) If the design does not promote accurate understanding of the capabilities of the technology, the operators will not use the technology effectively: the system may be switched off in conditions where it would be effective, or used for tasks or in contexts where its effectiveness may be very limited. 4) If an ineffective interaction design is implemented and put into use, a wide range of problems can ensue. Many involve lack of transparency into the system: operators may be unable or find it very difficult to determine a) the current state and changes of state of the automation or robot, b) the current state and changes in state of the system being controlled or acted on, and c) what actions by human or by system had what effects. 5) If the human interfaces for operation and control of robotic agents are not designed to accommodate the unique points of view and operating environments of both the human and the robotic agent, then effective human-robot coordination cannot be achieved

SERENITY: THE FUTURE OF COGNITIVE MODULATION FOR THE HYPER ENABLED OPERATOR

In the Special Operations community, cognitive enhancement and resilience is at the forefront of the 2035 Hyper Enabled Operator Program (HEO). The United States Special Operations Command’s vision is to combine cutting-edge communications and data capabilities into a next generation tactical system for the end user. Using algorithms and autonomous systems to enhance the ability to make rational decisions faster can ultimately determine life or death on the battlefield. Over the past several years, cognitive enhancement with the introduction of brain computer interface (BCI) technology has had major breakthroughs in the medical and science fields. This thesis looks to analyze BCI technology for future cognitive dominance and cognitive overmatch in the Hyper Enabled Operator. Machine-assisted cognitive enhancement is not beyond reach for special operations; throughout the research and after multiple interviews with subject matter experts, it has been concluded that interfaces using transcranial alternating current stimulation (tACS), median nerve stimulation (MNS), or several other exploratory procedures have been successful with enhancing cognition and reducing cognitive load. Special Operations should not shy away from transformational innovative technology or wait for commercial or lab-tested solutions. To start, Special Operations should foster avant-garde theories that provide solutions and evolve ideas into unsophisticated prototypes that can be fielded immediately.Major, United States ArmyApproved for public release. Distribution is unlimited

Adaptive Airborne Separation to Enable UAM Autonomy in Mixed Airspace

The excitement and promise generated by Urban Air Mobility (UAM) concepts have inspired both new entrants and large aerospace companies throughout the world to invest hundreds of millions in research and development of air vehicles, both piloted and unpiloted, to fulfill these dreams. The management and separation of all these new aircraft have received much less attention, however, and even though NASAs lead is advancing some promising concepts for Unmanned Aircraft Systems (UAS) Traffic Management (UTM), most operations today are limited to line of sight with the vehicle, airspace reservation and geofencing of individual flights. Various schemes have been proposed to control this new traffic, some modeled after conventional air traffic control and some proposing fully automatic management, either from a ground-based entity or carried out on board among the vehicles themselves. Previous work has examined vehicle-based traffic management in the very low altitude airspace within a metroplex called UTM airspace in which piloted traffic is rare. A management scheme was proposed in that work that takes advantage of the homogeneous nature of the traffic operating in UTM airspace. This paper expands that concept to include a traffic management plan usable at all altitudes desired for electric Vertical Takeoff and Landing urban and short-distance, inter-city transportation. The interactions with piloted aircraft operating under both visual and instrument flight rules are analyzed, and the role of Air Traffic Control services in the postulated mixed traffic environment is covered. Separation values that adapt to each type of traffic encounter are proposed, and the relationship between required airborne surveillance range and closure speed is given. Finally, realistic scenarios are presented illustrating how this concept can reliably handle the density and traffic mix that fully implemented and successful UAM operations would entail

Autonomous, Context-Sensitive, Task Management Systems and Decision Support Tools I: Human-Autonomy Teaming Fundamentals and State of the Art

Recent advances in artificial intelligence, machine learning, data mining and extraction, and especially in sensor technology have resulted in the availability of a vast amount of digital data and information and the development of advanced automated reasoners. This creates the opportunity for the development of a robust dynamic task manager and decision support tool that is context sensitive and integrates information from a wide array of on-board and off aircraft sourcesa tool that monitors systems and the overall flight situation, anticipates information needs, prioritizes tasks appropriately, keeps pilots well informed, and is nimble and able to adapt to changing circumstances. This is the first of two companion reports exploring issues associated with autonomous, context-sensitive, task management and decision support tools. In the first report, we explore fundamental issues associated with the development of an integrated, dynamic, flight information and automation management system. We discuss human factors issues pertaining to information automation and review the current state of the art of pilot information management and decision support tools. We also explore how effective human-human team behavior and expectations could be extended to teams involving humans and automation or autonomous systems

A generalizable method and case application for development and use of the Aviation Systems – Trust Survey (AS-TS).

Automated systems are integral in the development of modern aircraft, especially for complex military aircraft. Pilot Trust in Automation (TIA) in these systems is vital for optimizing the pilot-vehicle interface and ensuring pilots use the systems appropriately to complete required tasks. The objective of this research was to develop and validate a TIA scale and survey methodology to identify and mitigate trust deficiencies with automated systems for use in Army Aviation testing. There is currently no standard TIA assessment methodology for U.S. Army aviation pilots that identifies trust deficiencies and potential mitigations. A comprehensive literature review was conducted to identify prominent TIA factors present in similar studies. The compiled list of factors and associated definitions were used in a validation study that utilized the Analytic Hierarchy Process (AHP) as a pair-wise comparison tool to identify TIA factors most relevant to Army pilots. A notional survey, the Aviation Systems – Trust Survey (AS-TS), was developed from the identified factors and pilots were used as subjects in scenario-based testing to establish construct validity for the survey. Exploratory factor analysis was conducted after data collection and a validated survey was produced. A follow-on study interviewed Army test and evaluation experts to refine the survey methodology and ensure appropriate context for the recommended mitigations. A final packet was developed that included instructions for the rating scale, associated item definitions, and recommended mitigations for trust deficiencies. Future research will focus on other Army demographics to determine the generalizability of the AS-TS