The need to register data is abundant in applications such as: world modeling, part inspection and manufacturing, object recognition, pose estimation, robotic navigation, and reverse engineering. Registration occurs by aligning the regions that are common to multiple images. The largest difficulty in performing this registration is dealing with outliers and local minima while remaining efJicient. A commonly used technique, iterative closest point, is efficient but is unable to deal with outliers or avoid local minima. Another commonly used optimization algorithm, simulated annealing, is effective at dealing with local minima but is very slow. Therefore, the algorithm developed in this paper is a hybrid algorithm that combines the speed of iterative closest point with the robustness of simulated annealing. Additionally, a robust error function is incorporated to deal with outliers. This algorithm is incorporated into a complete modeling system that inputs two sets of range data, registers the sets, and outputs a composite model.

Robots are already being used in a variety of applications, including the military battlefield. As robotic technology continues to advance, those applications will increase, as will the demands on the associated network communication links. Two experiments investigated the effects of communication latency on the control of a robot across four Levels Of Automation (LOAs), (1) full teleoperation, (2) guarded teleoperation, (3) autonomous obstacle avoidance, and (4) full autonomy. Latency parameters studied included latency duration, latency variability, and the "direction" in which the latency occurs, that is from user-to-robot or from robot-to-user. The results indicate that the higher the LOA, the better the performance in terms of both time and number of errors made, and also the more resistant to the degrading effects of latency. Subjective reports confirmed these findings. Implications of constant vs. variable-latency, user-to-robot vs. robot-to-user latency, and latency duration are also discussed.

This paper describes a system which acquires 3D data and uses the data to track an eleven degree of freedom human model in real-time. Using four cameras we create a time-varying volumetric image (a visual hull) of whatever object is moving in the space observed by all four cameras. We are currently operating the sensor in a volume of approximately 500,000 voxels (1.5 inch cubes) at a rate of 25 Hz. We are able to track the upper body dynamics of a human within the workspace. The system is able to track the x, y position of the body, a torso rotation about the z axis, along with four rotations in each arm. Tracking occurs using a method we developed to be extremely fas~which allows both data acquisition and tracking to occur on one computer at a rate of 16 Hz. We also developed a calibration procedure, which allows the system to be reconfigured or even moved and to quickly be recalibrated. Furthermore the system utilizes another computer to visualize either the voxel data overlaid with the joint locations or to view a human avatar, both of which are driven in real-time. Lastly our system has been implemented to perform crane gesture recognition, and has been linked with a large robotic arm to simulate crane movements. Corresponding author

Much of the research on unmanned-vehicles (UVs) focuses on technology or interface design.This study however, investigated how to best support effective communication between the operator monitoring a UV and the Soldier in the field using that information to complete a mission. Several questions arise: Does the operator need to be co-located with Soldiers in the field or can he or she be in a more secure rearward location? Does the team need the capability to transmit visual images or is radio communication adequate? Is information from one type of UV better than others? Do real time mapping and tracking technologies increase situation awareness (SA)? To begin to answer these questions, military teams conducted rescue missions using the video game Raven Shield as a simulated battlefield. The analysis of performance data, self reports, and observations provide some valuable insight to these questions.

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