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Analysis, Modelling and Simulation for Human Movements

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Researcher Franck Multon explores the magic of simulating human motions and helps design the digital plants of tomorrow.


Bunraku experiment
 

< During an experiment on human motion in Rennes research center, volunteers are equipped with special sensors that help capture gait and behavior.


Associate professor in the Rennes 2 University LPBEM laboratory (1), Franck Multon is currently an invited researcher with the Irisa Bunraku project (2). He presented his research on computer generated images, animation, modeling and simulation during his HDR defence (3), on December 8, 2006.

Computerization techniques are used in several application fields in order to animate human-like figures, referred to as avatars or humanoids. Usually, they do not produce enough realistic trajectories. But things are changing. “Until now, computer simulation was based upon bone angle measurements. The process was hard because it had to deal with so many motion possibilities”, says Multon. With 206 bones, 650 muscles, tens of rotations, intertwined lengths of movable joints, connective tendons and ligaments, the human body is a complex machine driven by a string of laws such as gravity, mass, force, or inertia. Now, factor in a crumb of psychology and any human gait can turn into everything from flabby shuffling to flippant loping, adding complex niceties to the matter. Modelling and simulating the movements of such a mechanism is therefore rather… “challenging”.

The new approach takes a completely different strategy. It is based on a simplified skeleton with normalized global postural information and kinematic constraints that are intrinsically linked to the motion, such as ensuring foot-contact with the ground or reaching targets for grasping motions. The magic of it is “a phenomenal reduction of calculation time, Multon sums-up. It runs 100 times faster
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Constraints

 

Second originality: “the method is interactive. Many researchers need to know the full animation scenario in advance. This creates a problem: it can’t deal with unexpected events, like... changing the trajectory of an object that has to be grasped by the humanoid, for instance. In our system, we don’t need foreknowledge.”  A dramatic illustration of this dynamic adaptation is a video animation of avatars dancing on a waving floor. The motion looks natural, smooth and flawless. Such quality wasn’t available previously as most 3D animators provide their virtual character with specific size, weight and so on. Resulting drawback: the motions can hardly be animated on characters having different morphologies. On the opposite, Bunraku’s approach is based upon a morphology-independent representation of the skeleton. Thus, it allows the animation on the layman computer of hundreds of different characters, from lumberjack to ballerina, while at the moment most research centers can hardly animate more than one character at the time.

Fully operational virtual systems portend far-reaching applications in the real world. One of the promising sectors is training. “Virtual simulation is great for staff formation when function duties are complex, Multon remarks. Say you want to teach a helicopter mechanic how to perform maintenance on the chopper’s swashplate, there’s no way you can allow him to disassemble the blades just for training purpose. Virtual reality is simply much more convenient” and far less expensive. Cost-savings can be very significant in sectors such as the car industry or aeronautics, with thousands of workers to be trained every year. “Another aspect is the virtual prototype. For instance, an aircraft designer can place a synthetic human in the pilot’s seat in order to test cockpit ergonomics” and harvest loads of precious data on comfort, posture, reach, visibility, biomechanics, anthropometrics and strength. All this will help optimize accessibility and serviceability of components inside the cockpit.


LPBEM and Bunraku’s combined research have resulted in the creation of MKM (as: Manageable Kinematic Motions). This real-time animation engine automatically synchronizes, blends and adapts avatar motions. Rennes researchers are now part of the “digital factory” project within System@tic framework, a competitiveness cluster (4) in the Paris region. To put it mildly, “applications on the plant floor are bound to be terrific. But right now, it’s a a bit nightmarish. Quite often, when you accelerate the conveyor belt, the whole thing has to be reprogrammed.”



The goal of System@tic is to address the problem and define a platform for efficiently simulating industrial production. Operated by Dassault Systems, the scheme involves its subsidiary company Virtools whose eponymous 3D authoring software is about to become a standard in the VR industry. “MKM is a software building block that plugs into Virtools. We take constraints as input and deliver motions in output”, Multon explains.


Bunraku has an operational prototype featuring basic scenes. The software can accomodate large libraries of characters. “Next, we are going to test production line scenarios. Right now [through the avatar], we can make the [real] worker trainee puncture, screw or clip a spare part for instance. In a second phase, we ambition to have the trainee interact with the virtual colleagues. Both (real and virtual characters) could try to carry together a heavy and flexible piece of metal sheet for example.” In such interactive environment, there will be no advance knowledge of the scene evolution due to unexpected interventions by the user. “This will be the focus of our research in stage two of the Digital Factory project, a tender to which we are currently submitting.”

Bunraku experiment  

<Bunraku scientists during an experiment aiming a modelling crowd behavior in a narrow and semi-confined space like the entrance to a railway or subway station.

Such level of performance requires simulators to integrate cutting-edge perceptive, cognitive and reactive capabilities. “It’s challenging and… tricky, Multon warns. The trap occurs when the trainee achieves the assigned task in the virtual world but not… in real one!” That is why Bunraku strives at placing the user in the loop. “One of the problems we came across was testing the realism of our animations. A human body comprises 50-some rotations, not even mentioning the hands. Taking time into account leads to thousands of points. If there is a striking visual mistake, some unrealistic movement, it doesn't involve many points. May be just 50. Naked eye can spot the problem right away. But it's harder for computer.”


So how to automatically detect such problem with an accuracy similar to the one displayed by human eye? “The first approach consisted in inviting a panel of viewers to watch our animations and give us their feedback. Fine, but there is a lot human subjectivity into this.” When asked if an avatar is realistic, “people answer very differently, depending on their proclivity to play video games for instance.” So researchers wanted to bypass the subjectivity shelf and improve their validation protocol.

“That’s how we got the idea of having someone really interacting with our virtual being.” One of the experiments has focussed on the duel between two handball players: a real goalkeeper confronted to an avatar thrower. The intent is to compare the human gestures in the real and in the virtual experiment. The goal keeper is equipped with multiple sensors in order to provide a complete capture and modelling of his movements.

Results show “the goalkeeper reacts to all the thrower’s actions. If you slightly raise the throwing hand or if you slightly delay the release of the ball, then the human being adapts. He reacts! And by so doing, he validates the quality of the animation realism.” The phenomenon becomes all the more interesting when you learn that, prior to the experiment, “during the panel session, the goalkeeper watched the animation and found it… poorly convincing. He got us a mark of 2/20” although... reacting correctly and naturally to the animation.
Franck Multon
Franck Multon during HRD defence. Watch video.


Footnotes

(1) LPBEM  (Laboratoire de Physiologie et de Biomécanique de l'Exercice Musculaire) specializes in physiology and biomechanics of human motion.
(2) Formerly know as SIAMES and currently headed by Stephane Donikian, Bunraku project considers all methods needed for producing sequences of computer-generated images.
(3) The HDR (Habilitation à Diriger des Recherches) is an accreditation to supervise research.
(4) France has launched an industrial strategy focusing on the key factors of industrial competitiveness, particularly R&D-led innovation.



Transdisciplinarity key to breakthrough

“The big originality in all this is transdisciplinarity, Franck Multon remarks. And that’s new. Until now, biophysicists were doing some robotics. Neurophysicists were venturing into some computer science. And so on. But all in all, each discipline remained rather impervious to the others. I was offered the chance to work with the LPBEM laboratory under director Paul Delamarche who had a strong vision of transdisciplinarity.” This combine research brings together scientist from different fields. This motley crew of roboticians, mechanists, kinesiotherapists “work really together. We define a problem. We ask ourselves what are the protocols, how they can be integrated within a simulation model and how the results art to be validated. And ifs validation turns negative, we try again. Therefore, it’s a method.”






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Last modified 2007/02/21 10:48

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