Combining task and motion planning: challenges and guidelines

Masoumeh Mansouri, Federico Pecora, Peter Schüller

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Combined Task and Motion Planning (TAMP) is an area where no one-fits-all solution can exist. Many aspects of the domain, as well as operational requirements, have an effect on how algorithms and representations are designed. Frequently, trade-offs have to be made to build a system that is effective. We propose five research questions that we believe need to be answered to solve real-world problems that involve combined TAMP. We show which decisions and trade-offs should be made with respect to these research questions, and illustrate these on examples of existing application domains. By doing so, this article aims to provide a guideline for designing combined TAMP solutions that are adequate and effective in the target scenario.
Original languageEnglish
Article number637888
Number of pages12
JournalFrontiers in Robotics and AI
Publication statusPublished - 19 May 2021

Bibliographical note

Funding Information:
Federico Pecora is supported by the Swedish Knowledge Foundation (KKS) under the Semantic Robots research profile, and by Vinnova under projects AutoBoomer and AutoHauler. Peter Schüller is supported by the EU Horizon 2020 project AI4EU under grant agreement No. 825619.

Publisher Copyright:
© Copyright © 2021 Mansouri, Pecora and Schüller.


  • automated reasoning
  • industrial applications of robotics
  • integrative AI
  • knowledge representation
  • task and motion planning

ASJC Scopus subject areas

  • Computer Science Applications
  • Artificial Intelligence


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