Co-Optimization of Design and Fabrication Plans for Carpentry

ACM TOG, March 2022
BibTeX
@article{10.1145/3508499,
  author = {
    Zhao, Haisen and
    Willsey, Max and 
    Zhu, Amy and 
    Nandi, Chandrakana and 
    Tatlock, Zachary and 
    Solomon, Justin and 
    Schulz, Adriana},
  title = {Co-Optimization of Design and Fabrication Plans for Carpentry},
  year = {2022},
  issue_date = {June 2022},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  volume = {41},
  number = {3},
  issn = {0730-0301},
  url = {https://doi.org/10.1145/3508499},
  doi = {10.1145/3508499},
  journal = {ACM Trans. Graph.},
  month = {mar},
  articleno = {32},
  numpages = {13},
  keywords = {Fabrication, programming languages}
}

Abstract

Past work on optimizing fabrication plans given a carpentry design can provide Pareto-optimal plans trading off between material waste, fabrication time, precision, and other considerations. However, when developing fabrication plans, experts rarely restrict to a single design, instead considering families of design variations, sometimes adjusting designs to simplify fabrication. Jointly exploring the design and fabrication plan spaces for each design is intractable using current techniques. We present a new approach to jointly optimize design and fabrication plans for carpentered objects. To make this bi-level optimization tractable, we adapt recent work from program synthesis based on equality graphs (e-graphs), which encode sets of equivalent programs. Our insight is that subproblems within our bi-level problem share significant substructures. By representing both designs and fabrication plans in a new bag of parts (BOP) e-graph, we amortize the cost of optimizing design components shared among multiple candidates. Even using BOP e-graphs, the optimization space grows quickly in practice. Hence, we also show how a feedback-guided search strategy dubbed Iterative Contraction and Expansion on E-graphs (ICEE) can keep the size of the e-graph manageable and direct the search towards promising candidates. We illustrate the advantages of our pipeline through examples from the carpentry domain.