As landmines get harder to detect, the complexity of landmine detectors has also been increasing. To increase the probability of detection and decrease the false alarm rate of low metallic landmines, many detectors employ multiple sensing modalities, which include radar and metal detector. Unfortunately, the operator interface for these new detectors stays pretty much the same as for the older detectors. Although the amount of information that the new detectors acquire has increased significantly, the interface has been limited to a simple audio interface. We are currently developing a hybrid audiovisual interface for enhancing the overall performance of the detector. The hybrid audiovisual interface combines the simplicity of the audio output with the rich spatial content of the video display. It is designed to optimally present the output of the detector and also to give the proper feedback to the operator. Instead of presenting all the data to the operator simultaneously, the interface allows the operator to access the information as needed. This capability is critical to avoid information overload, which can significantly reduce the performance of the operator. The audio is used as the primary notification signal, while the video is used for further feedback, discrimination, localization and sensor fusion. The idea is to let the operator gets the feedback that he needs and enable him to look at the data in the most efficient way. We are also looking at a hybrid man-machine detection system which utilizes precise sweeping by the machine and powerful human cognitive ability. In such a hybrid system, the operator is free to concentrate on discriminant task, such as manually fusing the output of the different sensing modalities, instead of worrying about the proper sweep technique. In developing this concept, we have been using the virtual mien lane to validate some of these concepts. We obtained some very encouraging results form our preliminary test. It clearly shows that with the proper feedback, the performance of the operator can be improved significantly in a very short time.
KEYWORDS: Solar energy, Sensors, Solar cells, Environmental sensing, Air contamination, Global Positioning System, Carbon monoxide, Navigation systems, Skin, Gyroscopes
We believe that solar powered, autonomous airships with the capability to embark on extended duration sampling missions will serve as valuable tools for environmental science. In this paper, we outline our vision for an autonomous airship and discuss some of the applications for which such a craft would be well suited. We also report on our efforts to date to realize this vision. Specifically, we discuss the use of solar energy as a renewable source of power for airships. We also describe the configuration of a nine meter airship that we will use as a testbed for environmental sampling and autonomy research. We conclude by outlining directions for future research.
Landmine detection is a complex and highly dangerous task. Most demining operations are done using hand-held detectors, which means that the operator is always at risk of serious injury or death. One of the most important factor that determines the probability of detecting is the operator performance. Therefore, it is very important that we train the operator well and are able to assess their performance accurately. To achieve these objectives, we have been developing two training tools, the 3D tracker for real-time feedback during training, and the virtual mien lane for interactive training. We have been using the 3D tracker successfully to assess the performance of an operator as a prat of a successful training program.
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