Add Prediction Interface and linear position prediction model to Object Memory

Closes #91 (closed), #96 (closed).

Add linear position prediction to ObjectMemory Segment.

added hiwi module::armem labels

requested review from @RainerKartmann

assigned to @phesch

Thanks. Could you fix the problem with the inverse result?

added 1 commit

• c78693b4 - Minor changes to prediction code

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Looks good! I made some changes, but more on the style level.

As a refactoring, we could move the static function Eigen::Vector3d makeLinearPrediction() out to some general place. Maybe even SimoxUtility?

added 3 commits

• ee30cbb7 - Move linear prediction code to simox
• 6ff44348 - Shift timestamps around current time to avoid floating point imprecision
• ba6e6a5c - Merge branch 'linear-prediction-from-simox' into 'linear-prediction'

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added 1 commit

• 685ddf54 - Update to change in Simox

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I generalized the regression code in Simox. This changed the header and name of the regression class, so I updated the branch. I hope this won't create too many conflicts for you, as it is just a small change :)

added 5 commits

• 5f895988 - Make object pose prediction lookback a parameter
• 4ee022c4 - ObjMemory,Segment: Remove uses of armem::fromIce
• e75ac32e - Make getAvailableEngines return map instead of vec
• c102907d - MemoryViewer.cpp: Replace uses of armem::fromIce
• d16da192 - Add ObjectPose pred. to MemoryInterface

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added 4 commits

• 5104c3b5 - Implement suggestions from Gitlab MR
• bc2aad20 - Add time offset and window params to ObjMem Visu
• 864034c7 - Add fallbacks to linear prediction for edge cases
• ea64a429 - Make ObjPosClientEx visualize multiple predictions

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resolved all threads

Some things I noticed while working on this MR:

• Using std::stringstreams for error messages in BOs is not as great as we thought because it makes the BOs non-copyable, so you can't use them in vectors anymore.
• Last time, we discussed that predictions should use MemoryIDs that are resolved to the snapshot level. However, I think that object pose predictions require instance indices for disambiguation. In particular, the current code only works if every entity in the instance segment only has a single instance per snapshot. If it has multiple object instances, the predictions will mix up the different objects' poses. I'm not quite sure how to resolve this since ObjectIDs support arbitrary strings as instance names - armem only supports integers, so the conversion would be a little iffy.

Follow up:

Refactor prediction code from source/RobotAPI/libraries/armem_objects/server/instance/Segment.cpp into the library RobotAPIArmarXObjects (i.e. something like: ObjectPose predict(vector<ObjectPose> poses, time))

mentioned in issue #96 (closed)

added 47 commits

• ea64a429...60f6e344 - 44 commits from branch master
• 60d248e5 - Make PredictionResult error messages into strings
• a7eb5e0e - Merge branch 'master' into linear-prediction
• 238744af - Use entity name as object ID

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