Improve Handling of Symmetry

LMs currently recognize symmetry by making multiple observations in a row that are all consistent with a set of multiple poses. I.e. if new observations of an object do not eliminate any of a set of poses, then it is likely that these poses are equivalent/symmetric.

To make this more efficient and robust, we might store symmetric poses in long-term memory, updating them over time. In particular:

• Whenever symmetry is detected, the poses associated with the state could be stored for that object.
• Over-time, we can reduce or expand this list of symmetric poses, enabling the LM to establish with reasonable confidence that an object is in a symmetric pose as soon as the hypothesized poses fall within the list.

By developing an established list of symmetric poses, we might also improve voting on such symmetric poses - see Using Pose for Voting.