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hungpham2511 avatar hungpham2511 commented on July 28, 2024

Hi @mrunaljsarvaiya, thanks for using toppra.

The reason why toppra doesn't work as expected is that the input path is way too noisy. toppra requires a certain level of smoothness fo function properly.

Figure_1

This is the input file you throw to the algorithm. I would suggest you to try smoothing the path and try again. Thanks!

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mrunaljsarvaiya avatar mrunaljsarvaiya commented on July 28, 2024

Thank you!

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mrunaljsarvaiya avatar mrunaljsarvaiya commented on July 28, 2024

Is there a way to check whether the solver failed to produce a trajectory that meets the constraints without having to check the data ? And is there any metric to gauge what level of smoothness is needed?

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hungpham2511 avatar hungpham2511 commented on July 28, 2024

Very good question. I am sure there is a way, but I have not really thought about this in detail. Let me re-open this issue just to keep track of ideas for this new feature.

Any thoughts?

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mrunaljsarvaiya avatar mrunaljsarvaiya commented on July 28, 2024

I'm not too familiar with the theory behind toppra, why does the algorithm require smooth data points to work? I would have expected that if it sees a large spike/dip, a slower trajectory would be generated in that segment.

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hungpham2511 avatar hungpham2511 commented on July 28, 2024

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mrunaljsarvaiya avatar mrunaljsarvaiya commented on July 28, 2024

I have also noticed that if the trajectory generated by toppra is rerun through toppra, it produces a faster trajectory that deviates less from the limits. If this "feedback" loop is repeated multiple times, the trajectory gets faster and better abides by the limits with every iteration (I've tested this for a maximum of 3 iterations)

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github-actions avatar github-actions commented on July 28, 2024

Stale issue message

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