Simulation-based two stage sequencing of robotic assembly operations with deformable objects

Shir Ben-David, Ran Shneor, Shahar Zuler, Zachi Mann, Alex Greenberg, Sigal Berman

Research output: Contribution to journalConference articlepeer-review


Automatic generation of assembly sequences for products containing deformable objects, is an important step required for fully automated production. Robotic manipulation with deformable objects involves handling uncertainty related to object deformation which should be accounted for during assembly sequence planning (ASP). This work describes a two-stage sequencing planning of robotic assembly operations with deformable objects. ASP is an NP-hard problem and many heuristics have been developed for solving it. We suggest a method that improves a purely heuristic ASP by using a heuristic stage based on genetic algorithm (GA) and an additional robotic simulation stage. The method was demonstrated with products with deformable objects and promising results were achieved.

Original languageEnglish
Pages (from-to)175-180
Number of pages6
Issue number1
StatePublished - 1 Jan 2021
Event17th IFAC Symposium on Information Control Problems in Manufacturing INCOM 2021 - Budapest, Hungary
Duration: 7 Jun 20219 Jun 2021


  • Deformable objects
  • Genetic algorithm
  • Robotic assembly
  • Robotic simulation
  • Sequencing

ASJC Scopus subject areas

  • Control and Systems Engineering


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