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In hazardous situations involving the dispersion of chemical, biological, radiological, and nuclear pollutants, timely containment of the emission is critical. A contaminant disperses as a dynamically evolving plume into the atmosphere, introducing complex difficulties in predicting the dispersion trajectory and potential evacuation sites. Strategies for predictive modeling of rapid contaminant dispersion demand localization of the emission source, a task performed effectively via unmanned mobile-sensing platforms. With vast possibilities in sensor configurations and source-seeking algorithms, platform deployment in real-world applications involves much uncertainty alongside opportunity. This work aims to develop a plume source detection simulator to offer a reliable comparison of source-seeking approaches and performance testing of ground-based mobile-sensing platform configurations prior to experimental field testing. Utilizing ROS, Gazebo, MATLAB, and Simulink, a virtual environment is developed for an unmanned ground vehicle with a configurable array of sensors capable of measuring plume dispersion model data mapped into the domain. For selected configurations, gradient-based and adaptive exploration algorithms were tested for source localization using Gaussian dispersion models in addition to large eddy simulation models incorporating the effects of atmospheric turbulence. A unique global search algorithm was developed to locate the true source with overall success allowing for further evaluation in field experiments. From the observations obtained in simulation, it is evident that source-seeking performance can improve drastically by designing algorithms for global exploration while incorporating measurements of meteorological parameters beyond solely concentration (e.g. wind velocity and vorticity) made possible by the inclusion of high-resolution large eddy simulation plume data. [ABSTRACT FROM AUTHOR]

Many multi-agent systems (MASs) can be regarded as hybrid systems that contain continuous variables and discrete events exhibiting both continuous and discrete behavior. An MAS can accomplish complex tasks through communication, coordination, and cooperation among different agents. The complex, adaptive and dynamic characteristics of MASs can affect their stability that is critical for MAS performance. In order to analyze the stability of MASs, we propose a stability analysis method based on invariant sets and Lyapunov's stability theory. As a typical MAS, an unmanned ground vehicle formation is used to evaluate the proposed method. We design discrete modes and control polices for the MAS composed of unmanned ground vehicles to guarantee that the agents can cooperate with each other to reliably achieve a final assignment. Meanwhile, the stability analysis is given according to the definition of MAS stability. Simulation results illustrate the feasibility and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The article presents a study that examines skill development and workload among those piloting teleoperated unmanned ground vehicles (UGVs) through openings of different widths using the so-called cornering law. Two groups of novices operated UGVs using either a first-person or third-person-overhead view. In both cases the cornering law was successful in modeling how aperture width affected driving performance.

Objective: The effect of viewpoint on the navigation of complex terrain and on spatial awareness was examined with the use of a simulated remotely operated vehicle.Background: The ability to build terrain models in real time may soon allow remote vehicular control from any viewpoint. A virtual tether couples the viewpoint to the vehicle’s position and orientation, but shows more of the terrain than a fully immersive egocentric display. In this sense, it provides visual momentum by providing a view that incorporates egocentric and exocentric qualities.Method: For this study, 12 participants navigated a simulated vehicle across complex virtual terrain using five different display viewpoints: egocentric, dynamic tether, rigid tether, 3-D exocentric, and 2-D exocentric. While navigating, participants had to avoid being seen by simulated enemy units. After the navigation task, participants’ spatial awareness was assessed using a recognition task.Results: The tethered displays minimized the time during which the participant’s vehicle was visible to enemy positions. The egocentric display was more effective than exocentric displays (2-D or 3-D) for navigation, and the exocentric displays were more effective than egocentric for time seen during navigation and the recognition task. The tethered displays produced intermediate results for navigation and recognition.Conclusion: Viewpoint tethering produced the most effective displays for minimizing time seen, but tethered displays were less effective than egocentric and exocentric displays for navigation and recognition, respectively.Application: A tethered display is recommended for applications in which it is necessary to understand the relation of nearby locations to one’s own location. [ABSTRACT FROM AUTHOR]