Driving on Mars with RSVP

The rover sequencing and visualization program (RSVP) suite of tools has been a critical factor in the success of the Mars exploration rover (MER) missions. It would be impossible to prepare the large command loads each sol without the capabilities that it possesses. It has proven to be robust and easy to use and capable of answering key questions about sequence validity and constraints. Certainly, training is required to use RSVP, but this is primarily in the general area of command sequencing and rover operations. Once these concepts are understood, RSVP feels natural for building sequences. RSVP has met its prime requirements of supporting rapid assimilation and understanding of the terrain and operational constraints, rapid sequence generation and validation, and production of documentation and archival products. This can be seen in the very limited number of sols lost due to errors in the command sequences. The success of the MER mission and the tremendous amount of science data collected attest to the capability of RSVP.     

Multi-variable nonlinear MPC of an ill-conditioned distillation column

A quasi-ARMAX modelling scheme is studied for the purpose of modelling and control of multi-variable ill-conditioned and nonlinear processes. A distillation column is used as a case-study. The modelling technique is in this paper extended for use in the multi-variable case. Also, the nonlinear directionality of the distillation column is analyzed and illustrated. The nonlinear MPC formulation with the quasi-ARMAX model used for prediction is studied for control of the distillation column at different operating regions.     

Computational performance of a parallelized three-dimensional high-order spectral element toolbox

In this paper, a comprehensive performance review of an MPI-based high-order three-dimensional spectral element method C++ toolbox is presented. The focus is put on the performance evaluation of several aspects with a particular emphasis on the parallel efficiency. The performance evaluation is analyzed with the help of a time prediction model based on a parameterization of the application and the hardware resources. Two tailor-made benchmark cases in computational fluid dynamics (CFD) are introduced and used to carry out this review, stressing the particular interest for clusters with up to thousands of cores. Some problems in the parallel implementation have been detected and corrected. The theoretical complexities with respect to the number of elements, to the polynomial degree, and to communication needs are correctly reproduced. It is concluded that this type of code has a nearly perfect speedup on machines with thousands of cores, and is ready to make the step to next-generation petaFLOP machines.     

Navigation Aided Image Processing in UAV Surveillance: Preliminary Results and Design of an Airborne Experimental System

This paper describes an airborne reconfigurable measurement system being developed at Swedish Defence Research Agency (FOI), Sensor Technology, Sweden. An image processing oriented sensor management architecture for UAV (unmanned aerial vehicles) IR/EO-surveillance is presented. Some preliminary results of navigation aided image processing in UAV applications are demonstrated, such as SLAM (simultaneous localization and mapping), structure from motion and geolocation, target tracking, and detection of moving objects. The design goal of the measurement system is to emulate a UAV-mounted sensor gimbal using a stand-alone system. The minimal configuration of the system consists of a gyro-stabilized gimbal with IR and CCD sensors and an integrated high-performance navigation system. The navigation system combines dGPS real-time kinematics (RTK) data with data from an inertial measurement unit (IMU) mounted with reference to the optical sensors. The gimbal is to be used as an experimental georeferenced sensor platform, using a choice of carriers, to produce military relevant image sequences for studies of image processing and sensor control on moving surveillance and reconnaissance platforms. Furthermore, a high resolution synthetic environment, developed for sensor simulations in the visual and infrared wavelengths, is presented. © 2004 Wiley Periodicals, Inc.     

Yield and transient effects during the plastic deformation of solid polymers

Tensile tests were performed on seven commercial polymers at 22° C and at constant true strain rates of 10^–4 to 10^–1 sec^–1. The constant strain rates were imposed on the minimum section of each sample with the aid of a diametral transducer, an exponential function generator and a closed-loop hydraulic testing machine. The polymers investigated were: high and low density polyethylene, polytetrafluoroethylene, polypropylene. polyvinylchloride and polyamide 6 and 66. True yield drops were observed in the rigid glassy polymers, whereas yielding was more gradual in the semi-crystalline or plasticized polymers. Strain rate change tests were also performed, during which one order of magnitude increases and decreases were imposed on the specimens. Normal transients were observed at small strains in the samples containing a rubbery phase, while the transients were of an inverse nature in the samples containing a glassy phase. With an increase in the strain at which the change was initiated, the normal transients changed in character to inverse. Transient tests were also performed in which straining was interrupted to permit a period of stress relaxation or of holding in the unloaded condition prior to the resumption of straining. A quantitative model is proposed, based on the dynamics of plastic waves which accounts for the transition from normal to inverse transient behaviour with increasing strain, and also explains the opposite effects of stress relaxation and of specimen unloading on the restraining transients.     

Variance analysis of identified linear MISO models having spatially correlated inputs,with application to parallel Hammerstein models

This contribution concerns variance analysis of linear multi-input single-output models when the inputs are temporally white but where different inputs may be correlated. An expression is provided for the variance of a linearly parametrized estimate of the frequency response function from one block, i.e. from one input to the output. In particular, this expression reveals that the variance increases in one block when the number of estimated parameters in another block is increased, but levels off when the number of parameters in the other block reaches the number of parameters in the block in question. It also quantifies exactly how correlation between inputs affects the resulting accuracy and a graphical representation is provided for this purpose. The results are applicable to parallel MISO Hammerstein models when the nonlinearities are known and generalize an existing variance expression for this type of model.     

Investigating haptic distance-to-break using linear and nonlinear materials in a simulated minimally invasive surgery task

Accurate detection of mediated haptic information in minimally invasive surgery (MIS) is critical for applying appropriate force magnitudes onto soft tissue with the aim of minimising tissue trauma. Force perception in MIS is a dynamic process, with surgeons’ administration of force into tissue revealing information about the remote surgical site which further informs the surgeons’ haptic interactions. The relationship between applied force and material deformation rate provides biomechanical information specifying the deformation distance remaining until a tissue will fail: which is termed distance-to-break (DTB). The current study demonstrates that observers can detect DTB while deforming simulated tissues and stop before reaching the tissues’ failure points. The design of training simulators, control devices and automated robotic systems for applications outside of MIS is discussed.

Practitioner Summary: In MIS, haptic information is critical for applying appropriate forces onto soft tissue to minimise tissue trauma. Observers used force information to detect how far they could deform a virtual tissue before it would break. The design of training simulators, control devices and automated robotic systems is discussed.     

Style-Controllable Speech-Driven Gesture Synthesis Using Normalising Flows

Automatic synthesis of realistic gestures promises to transform the fields of animation, avatars and communicative agents. In off-line applications, novel tools can alter the role of an animator to that of a director, who provides only high-level input for the desired animation; a learned network then translates these instructions into an appropriate sequence of body poses. In interactive scenarios, systems for generating natural animations on the fly are key to achieving believable and relatable characters. In this paper we address some of the core issues towards these ends. By adapting a deep learning-based motion synthesis method called MoGlow, we propose a new generative model for generating state-of-the-art realistic speech-driven gesticulation. Owing to the probabilistic nature of the approach, our model can produce a battery of different, yet plausible, gestures given the same input speech signal. Just like humans, this gives a rich natural variation of motion. We additionally demonstrate the ability to exert directorial control over the output style, such as gesture level, speed, symmetry and spacial extent. Such control can be leveraged to convey a desired character personality or mood. We achieve all this without any manual annotation of the data. User studies evaluating upper-body gesticulation confirm that the generated motions are natural and well match the input speech. Our method scores above all prior systems and baselines on these measures, and comes close to the ratings of the original recorded motions. We furthermore find that we can accurately control gesticulation styles without unnecessarily compromising perceived naturalness. Finally, we also demonstrate an application of the same method to full-body gesticulation, including the synthesis of stepping motion and stance.     

Uzawa Conjugate Gradient Domain Decomposition Methods for Coupled Stokes Flows

This paper deals with nonoverlapping domain decomposition methods for two coupled Stokes flows, based on the duality theory. By introducing a fictitious variable in the transmission condition and using saddle-point equations, the problem is restated as a linearly constrained maximization problem. According to whether constraints are uncoupled Stokes problems or uncoupled Poisson problems, two Uzawa-type domain decomposition algorithms are proposed. The results of some numerical experiments on a model problem are given.