[ODE] How do you determine the quality of a physics library?

[ron taņeza]

--

On Wed, 13 Mar 2002 23:54:05  
 Russ Smith wrote:
>no one simulation method is "better". they all have their pros and
>cons. consult chapter 1.1 of the manual to see what ODE is good at.
>ODE's big disadvantage is that it's relatively slow for big systems.
>
Is this something like a design tradeoff? ex. more stability means less accuracy? Anyway, I haven't tried other physics SDKs, except viewing the demos that came with dynamechs, so I wouldn't know. 

What's the main difference among the simulation methods anyway? Is it the algorithm for solving the equations? the method of integration? and does 'integration' here refer to the calculus term?

>this question is tricky. ODE simulates to 1st order accuracy, which
>is a quantifiable way of measuring how "good" it is. but really we
>should be measuring how close ODE will let you come to modeling a
>real-world system ... e.g. 10th order accuracy to an ideal system
>is no good if that ideal system doesn't work at all like the
>corresponding real world system.
>
Yes, I get what you're saying. The math part (i.e. solving equations) is really just a part of it. Knowing what equations to solve, or how to model the system, is important, too.

>wave your hands a lot and use big words. that's what i do.
>
hehe.. I needn't have bothered. The only question they asked after the presentation was, "What was the division of labor again?" I think the physics really impressed them. And that's just wheeled mobots. They should see your walking biped, or Nate's Juice models. :)

>first you have to define what you mean by "correct". this is not
>necessarily very easy. if you mean "behaves as close as possible to
>the corresponding real system", do you mean:
>
>  1. the state space trajectories of the real and simulated systems
>     match as closely as possible. but what if the systems are chaotic?
>  2. the same qualitative behaviors (behavior modes) are observed in
>     both systems. but then defining "sameness" is tricky here too.
>
uhmmm, I don't understand the technical terms. I did study state space modelling for control systems (i.e. x-dot = Ax + Bu, y = Cx + Du), but I don't know if it's similar to what you wrote in #1.

Anyway, our project's finally finished. You can program a wheeled mobot to respond to sensor readings. You choose between a car-drive or differential-drive chassis, then you attach bump, IR or sonar sensors, then you program the mobot's behaviors in a text file. You can also create maps -- boxes, spheres, capped cylinders, and ramps, either 'bodies' (objects with mass) or 'geoms' (immovable). I'll release the source maybe next week, after we've finished the docu.

And it all wouldn't have been possible without ODE. Thanks a lot, Russ!


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