Dense Robotic Packing of Irregular and Novel 3D Objects

Fan Wang, Kris Hauser

Research output: Contribution to journalArticlepeer-review


Recent progress in the field of robotic manipulation has generated interest in fully automatic object packing in warehouses. This article presents a formulation of the robotic packing problem that ensures stability of the object pile during packing and the feasibility of the robot motion while maximizing packing density. A constructive packing algorithm is proposed to address this problem by searching over the space of item positions and orientations. Moreover, a new heightmap minimization heuristic is shown to outperform existing heuristics in the literature in the presence of nonconvex objects. Two strategies for improving the robustness of executed packing plans are also proposed: 1) conservative planning ensures plan feasibility under uncertainty in model parameters; and 2) closed-loop packing uses vision sensors to measure placement errors and replans to correct for them. The proposed planner and error mitigation strategies are evaluated in simulation and on a state-of-the-art physical packing testbed. Experiments demonstrate that the proposed planner generates high-quality packing plans, and the error mitigation strategies improve success rates beyond an open-loop baseline from 83% to 100% on five-item orders.

Original languageEnglish (US)
Pages (from-to)1160-1173
Number of pages14
JournalIEEE Transactions on Robotics
Issue number2
StatePublished - Apr 1 2022


  • Bin packing
  • robotics
  • warehouse automation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering


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