Aerospace medicine and biology: A continuing bibliography with indexes (supplement 320)

This bibliography lists 125 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during January, 1989. Subject coverage includes: aerospace medicine and psychology, life support systems and controlled environments, safety equipment, exobiology and extraterrestrial life, and flight crew behavior and performance

Unmanned systems interoperability standards

Over the past several years, there has been rapid growth in the development and employment of unmanned systems in military and civilian endeavors. Some military organizations have expressed concern that these systems are being fielded without sufficient capabilities to interoperate with existing systems. Despite recognition of this requirement, interoperability efforts remain diverse and disjointed across the United States and internationally. The Naval Postgraduate School (NPS), Monterey, California, was sponsored by the U.S. Office of the Secretary of Defense (OSD) Joint Ground Robotics Enterprise (JGRE) in Fiscal Year 2016 (FY16) to explore (1) enhancement of robotics education; (2) improved representation of robotic systems in combat simulations; and (3) interoperability standards for military robotics systems. This report discusses work performed in FY16 to identify current and emerging interoperability standards for unmanned systems, including interactions of robotic systems with command and control (C2) and simulation systems. The investigation included assessment of the applicability of standardization activities in the Simulation Interoperability Standards Organization (SISO) in its development of the Phase 1 Coalition Battle Management Language (C-BML) and currently in-progress Command and Control Systems - Simulation Systems Interoperation (C2SIM) standardization efforts. The report provides a recommended approach, standards, activities, and timetable for a cross-system communications roadmap.Secretary of Defense Joint Ground Robotics Enterprise, 3090 Defense Pentagon, Room 5C756, Washington, DC 20301Office of the Secretary of Defense Joint Ground Robotics Enterprise.Approved for public release; distribution is unlimited

Intelligent Robotic Behaviors for Landmine Detection and Marking

This article discusses experimental results achieved with a robotic countermine system that utilizes autonomous behaviors and a mixed-initiative control scheme to address the challenges of detecting and marking buried landmines. By correlating aerial imagery and ground-based robot mapping, the interface provides context for the operator to task the robot. Once tasked, the robot can perform the search and detection task without the use of accurate global positioning system information or continuous communication with the operator. Results show that the system was able to find and mark landmines with a very low level of human involvement. In addition, the data indicates that the robotic system may be able to decrease the time to find mines and increase the detection, accuracy and reliability

Mixed Initiative Systems for Human-Swarm Interaction: Opportunities and Challenges

Human-swarm interaction (HSI) involves a number of human factors impacting human behaviour throughout the interaction. As the technologies used within HSI advance, it is more tempting to increase the level of swarm autonomy within the interaction to reduce the workload on humans. Yet, the prospective negative effects of high levels of autonomy on human situational awareness can hinder this process. Flexible autonomy aims at trading-off these effects by changing the level of autonomy within the interaction when required; with mixed-initiatives combining human preferences and automation's recommendations to select an appropriate level of autonomy at a certain point of time. However, the effective implementation of mixed-initiative systems raises fundamental questions on how to combine human preferences and automation recommendations, how to realise the selected level of autonomy, and what the future impacts on the cognitive states of a human are. We explore open challenges that hamper the process of developing effective flexible autonomy. We then highlight the potential benefits of using system modelling techniques in HSI by illustrating how they provide HSI designers with an opportunity to evaluate different strategies for assessing the state of the mission and for adapting the level of autonomy within the interaction to maximise mission success metrics.Comment: Author version, accepted at the 2018 IEEE Annual Systems Modelling Conference, Canberra, Australi

The Role of Human-Automation Consensus in Multiple Unmanned Vehicle Scheduling

Objective: This study examined the impact of increasing automation replanning rates on operator performance and workload when supervising a decentralized network of heterogeneous unmanned vehicles. Background: Futuristic unmanned vehicles systems will invert the operator-to-vehicle ratio so that one operator can control multiple dissimilar vehicles connected through a decentralized network. Significant human-automation collaboration will be needed because of automation brittleness, but such collaboration could cause high workload. Method: Three increasing levels of replanning were tested on an existing multiple unmanned vehicle simulation environment that leverages decentralized algorithms for vehicle routing and task allocation in conjunction with human supervision. Results: Rapid replanning can cause high operator workload, ultimately resulting in poorer overall system performance. Poor performance was associated with a lack of operator consensus for when to accept the automation’s suggested prompts for new plan consideration as well as negative attitudes toward unmanned aerial vehicles in general. Participants with video game experience tended to collaborate more with the automation, which resulted in better performance. Conclusion: In decentralized unmanned vehicle networks, operators who ignore the automation’s requests for new plan consideration and impose rapid replans both increase their own workload and reduce the ability of the vehicle network to operate at its maximum capacity. Application: These findings have implications for personnel selection and training for futuristic systems involving human collaboration with decentralized algorithms embedded in networks of autonomous systems.Aurora Flight Sciences Corp.United States. Office of Naval Researc

Using a Multiobjective Approach to Balance Mission and Network Goals within a Delay Tolerant Network Topology

This thesis investigates how to incorporate aspects of an Air Tasking Order (ATO), a Communications Tasking Order (CTO), and a Network Tasking Order (NTO) within a cognitive network framework. This was done in an effort to aid the commander and or network operator by providing automation for battlespace management to improve response time and potential inconsistent problem resolution. In particular, autonomous weapon systems such as unmanned aerial vehicles (UAVs) were the focus of this research This work implemented a simple cognitive process by incorporating aspects of behavior based robotic control principles to solve the multi-objective optimization problem of balancing both network and mission goals. The cognitive process consisted of both a multi-move look ahead component, in which the future outcomes of decisions were estimated, and a subsumption decision making architecture in which these decision-outcome pairs were selected so they co-optimized the dual goals. This was tested within a novel Air force mission scenario consisting of a UAV surveillance mission within a delay tolerant network (DTN) topology. This scenario used a team of small scale UAVs (operating as a team but each running the cognitive process independently) to balance the mission goal of maintaining maximum overall UAV time-on-target and the network goal of minimizing the packet end-to-end delays experienced within the DTN. The testing was accomplished within a MATLAB discrete event simulation. The results indicated that this proposed approach could successfully simultaneously improve both goals as the network goal improved 52% and the mission goal improved by approximately 6%