CMU paper defines solver-sufficient symbols to cut hybrid robot planning cost
Yiyuan Pan · hf · 2026-10-22
A CMU/UPenn paper takes an inference-algorithm-centric view of symbol design in robot planning. It defines usefulness — good symbols expose discrete commitments that simplify solving the continuous optimization — and introduces solver-sufficient symbolization for finite-horizon piecewise-affine systems, with a counterexample-guided symbol invention algorithm. Extending to neural-network energy functions, experiments on simulated and real-robot tasks show reduced solving cost, preserved solution quality, and improved interpretability.
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