Operator Objective Function Guidance for a Real-time Unmanned Vehicle Scheduling Algorithm

Advances in autonomy have made it possible to invert the typical operator-to-unmanned-vehicle ratio so that asingle operator can now control multiple heterogeneous unmanned vehicles. Algorithms used in unmanned-vehicle path planning and task allocation typically have an objective function that only takes into account variables initially identified by designers with set weightings. This can make the algorithm seemingly opaque to an operator and brittle under changing mission priorities. To address these issues, it is proposed that allowing operators to dynamically modify objective function weightings of an automated planner during a mission can have performance benefits. A multiple-unmanned-vehicle simulation test bed was modified so that operators could either choose one variable or choose any combination of equally weighted variables for the automated planner to use in evaluating mission plans. Results from a human-participant experiment showed that operators rated their performance and confidence highest when using the dynamic objective function with multiple objectives. Allowing operators to adjust multiple objectives resulted in enhanced situational awareness, increased spare mental capacity, fewer interventions to modify the objective function, and no significant differences in mission performance. Adding this form of flexibility and transparency to automation in future unmanned vehicle systems could improve performance, engender operator trust, and reduce errors.Aurora Flight Sciences, U.S. Office of Naval Researc

Realistic deployment of hybrid wireless sensor networks based on ZigBee and LoRa for search and rescue applications

Search and Rescue operations in emergency response to natural or human catastrophes have the main objective of locating and rescuing potential victims as fast as possible, thus quick response and accurate actions are mandatory. While standard communications may be affected, a Wireless Sensor Network can be deployed to support the rescue team. This kind of network allows data acquisition close to events and enables persistence over time, among other advantages. However, enhancements must be made to improve the adaptation to this kind of scenario. This work presents two Hybrid Wireless Sensor Networks, based on ZigBee and LoRa, developed to address some of the challenges that Search and Rescue operations pose to the use of Wireless Sensor Networks, and tested in realistic scenarios in cooperation with first responders. Likewise, several software developments that increase the performance of the networks are described. Finally, the conclusions presented, and the lessons learnt are supported by a high amount of data, gathered in realistic exercises in cooperation with civilian and military first responders.Spanish Project RTI2018-093421-B-I0

Visuo-spatial Abilities In Remote Perception: A Meta-analysis Of Empirical Work

Meta-analysis was used to investigate the relationship between visuo-spatial ability and performance in remote environments. In order to be included, each study needed to examine the relationship between the use of an ego-centric perspective and various dimensions of performance (i.e., identification, localization, navigation, and mission completion time). The moderator analysis investigated relationships involving: (a) visuo-spatial construct with an emphasis on Carroll’s (1993) visualization (VZ) factor; (b) performance outcome (i.e., identification, localization, navigation, and mission completion time); (c) autonomy to support mission performance; (d) task type (i.e., navigation vs. reconnaissance); and (e) experimental testbed (i.e., physical vs. virtual environments). The process of searching and screening for published and unpublished analyses identified 81 works of interest that were found to represent 50 unique datasets. 518 effects were extracted from these datasets for analyses. Analyses of aggregated effects (Hunter & Schmidt, 2004) found that visuo-spatial abilities were significantly associated with each construct, such that effect sizes ranged from weak (r = .235) to moderately strong (r = .371). For meta-regression (Borenstein, Hedges, Figgins, & Rothstein, 2009; Kalaian & Raudenbush, 1996; Tabachnick & Fidell, 2007), moderation by visuo-spatial construct (i.e., focusing on visualization) was consistently supported for all outcomes. For at least one of the outcomes, support was found for moderation by test, the reliability coefficient of a test, autonomy (i.e. to support identification, localization, and navigation), testbed (i.e., physical vs. virtual environment), intended domain of application, and gender. These findings illustrate that majority of what researchers refer to as “spatial ability” actually uses measures that load onto Carroll’s (1993) visualization (VZ) factor. The associations between this predictor and all performance outcomes were significant, but the significant iv variation across moderators highlight important issues for the design of unmanned systems and the external validity of findings across domains. For example, higher levels of autonomy for supporting navigation decreased the association between visualization (VZ) and performance. In contrast, higher levels of autonomy for supporting identification and localization increased the association between visualization (VZ) and performance. Furthermore, moderation by testbed, intended domain of application, and gender challenged the degree to which findings can be expected to generalize across domains and sets of participants

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

Towards Mixed-Initiative Human–Robot Interaction: Assessment of Discriminative Physiological and Behavioral Features for Performance Prediction

The design of human–robot interactions is a key challenge to optimize operational performance. A promising approach is to consider mixed-initiative interactions in which the tasks and authority of each human and artificial agents are dynamically defined according to their current abilities. An important issue for the implementation of mixed-initiative systems is to monitor human performance to dynamically drive task allocation between human and artificial agents (i.e., robots). We, therefore, designed an experimental scenario involving missions whereby participants had to cooperate with a robot to fight fires while facing hazards. Two levels of robot automation (manual vs. autonomous) were randomly manipulated to assess their impact on the participants’ performance across missions. Cardiac activity, eye-tracking, and participants’ actions on the user interface were collected. The participants performed differently to an extent that we could identify high and low score mission groups that also exhibited different behavioral, cardiac and ocular patterns. More specifically, our findings indicated that the higher level of automation could be beneficial to low-scoring participants but detrimental to high-scoring ones, and vice versa. In addition, inter-subject single-trial classification results showed that the studied behavioral and physiological features were relevant to predict mission performance. The highest average balanced accuracy (74%) was reached using the features extracted from all input devices. These results suggest that an adaptive HRI driving system, that would aim at maximizing performance, would be capable of analyzing such physiological and behavior markers online to further change the level of automation when it is relevant for the mission purpose

A Control Architecture for Unmanned Aerial Vehicles Operating in Human-Robot Team for Service Robotic Tasks

In this thesis a Control architecture for an Unmanned Aerial Vehicle (UAV) is presented. The aim of the thesis is to address the problem of control a flying robot operating in human robot team at different level of abstraction. For this purpose, three different layers in the design of the architecture were considered, namely, the high level, the middle level and the low level layers. The special case of an UAV operating in service robotics tasks and in particular in Search&Rescue mission in alpine scenario is considered. Different methodologies for each layer are presented with simulated or real-world experimental validation

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 376)

This bibliography lists 265 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during Jun. 1993. Subject coverage includes: aerospace medicine and physiology, life support systems and man/system technology, protective clothing, exobiology and extraterrestrial life, planetary biology, and flight crew behavior and performance

Dynamic human-computer collaboration in real-time unmanned vehicle scheduling

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2010.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student submitted PDF version of thesis.Includes bibliographical references (p. 123-127).Advances in autonomy have made it possible to invert the operator-to-vehicle ratio so that a single operator can control multiple heterogeneous Unmanned Vehicles (UVs). This autonomy will reduce the need for the operator to manually control each vehicle, enabling the operator to focus on higher-level goal setting and decision-making. Computer optimization algorithms that can be used in UV path-planning and task allocation usually have an a priori coded objective function that only takes into account pre-determined variables with set weightings. Due to the complex, time-critical, and dynamic nature of command and control missions, brittleness due to a static objective function could cause higher workload as the operator manages the automation. Increased workload during critical decision-making could lead to lower system performance which, in turn, could result in a mission or life-critical failure. This research proposes a method of collaborative multiple UV control that enables operators to dynamically modify the weightings within the objective function of an automated planner during a mission. After a review of function allocation literature, an appropriate taxonomy was used to evaluate the likely impact of human interaction with a dynamic objective function. This analysis revealed a potential reduction in the number of cognitive steps required to evaluate and select a plan, by aligning the objectives of the operator with the automated planner. A multiple UV simulation testbed was modified to provide two types of dynamic objective functions. The operator could either choose one quantity or choose any combination of equally weighted quantities for the automated planner to use in evaluating mission plans. To compare the performance and workload of operators using these dynamic objective functions against operators using a static objective function, an experiment was conducted where 30 participants performed UV missions in a synthetic environment. Two scenarios were designed, one in which the Rules of Engagement (ROEs) remained the same throughout the scenario and one in which the ROEs changed. The experimental results showed that operators rated their performance and confidence highest when using the dynamic objective function with multiple objectives. Allowing the operator to choose multiple objectives resulted in fewer modifications to the objective function, enhanced situational awareness (SA), and increased spare mental capacity. Limiting the operator to choosing a single objective for the automated planner led to superior performance for individual mission goals such as finding new targets, while also causing some violations of ROEs, such as destroying a target without permission. Although there were no significant differences in system performance or workload between the dynamic and static objective 4 functions, operators had superior performance and higher SA during the mission with changing ROEs. While these results suggest that a dynamic objective function could be beneficial, further research is required to explore the impact of dynamic objective functions and changing mission goals on human performance and workload in multiple UV control.by Andrew S. Clare.S.M