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ponents of the robotic vchicle mechanical subsystem, senson, on-board control software, as well as the environment This paper describes recent developments in the ROAMS and terraidvehicle interactions. ROAMS provides interfaces physics-based simulator for planetary surface exploration to close many different rover control loops ranging from rover vehicles. ROAMS includes models for various subsys-IOW level motor control, locomotion estimation and control, tems and components of the vehicle including its mechani-to navigation and .,ision control loops shown in Figure 1. cal subsystem, sensors. on-board resources, on-board control The ROAMS 'simulator is being used for stand-alone simsoftware, the terrain environment and terraidvehicle interactions. The ROAMS simulator can be used in stand-alone mode, for closed-loop simulation with on-board software or for operator-in-the-loop simulations. 0-7803-8155-6/04/$17.00 @ZW4 IEEE 0-7803-8155-6/04/$17.00 02004 IEEE

Structured Light Plethysmography (SLP) is a novel non-invasive method that uses structured light to perform pulmonary function testing that does not require physical contact with a patient. The technique produces an estimate of chest wall volume changes over time. A patient is observed continuously by two cameras and a known pattern of light (i.e. structured light) is projected onto the chest using an off-the-shelf projector. Corner features from the projected light pattern are extracted, tracked and brought into correspondence for both camera views over successive frames. A novel self calibration algorithm recovers the intrinsic and extrinsic camera parameters from these point correspondences. This information is used to reconstruct a surface approximation of the chest wall and several novel ideas for 'cleaning up' the reconstruction are used. The resulting volume and derived statistics (e.g. FVC, FEV) agree very well with data taken with a spirometer.

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This paper considers the problem of taking marker locations from optical motion capture data to identify and parameterise the underlying human skeleton structure and motion over time. It is concerned with real-time algorithms suitable for use within a visual feedback system. A common problem in motion capture is marker occlusion. Most current methods are only useful for offline processing or become ineffective when a significant portion of markers are missing for a long period of time. This paper presents a prediction algorithm, using a Kalman filter approach in combination with inferred information from neighbouring markers, to provide a continuous flow of data. The results are accurate and reliable even in cases where all markers on a limb are occluded, or one or two markers are not visible for a large sequence of frames. Pre-defined models are not required and skeleton fitting to this complete data can then be updated in real-time.