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About this Wiki

Following the RSS2016 TAMP workshop, a discussion group (see Contributors below) was created to come up with a methodology and a set of benchmark problems for TAMP. Our discussions and the actual benchmarks can be found in the TAMP FO-DA section in the Contents menu. More details can be found in this paper. Our approach was to start with a set of problems which can be handled by the largest number of existing systems, by identifying the least common denominator for requirements and problem specification, at logical and geometric levels.

However, since TAMP covers a wide range of problems, it was not possible to come up with a set of benchmarks for all types of TAMP problems. Therefore the Contents of the wiki is organized according to subclasses of TAMP. If you find the assumptions and requirements for TAMP FO-DA incompatible with the type of problems you are interested in, please contribute by creating your own benchmark set in the Contents section. Candidate subclasses are suggested:


How to use this wiki

  • This page is powered by MediaWiki, you can find instructions for editing pages here.
  • Do not modify a page for which you have not taken part in discussions.
  • Do not create a benchmark set on your own: this has to be a collaborative work involving other researchers.
  • For discussions, use the wiki "Discussion" tab, or set up a discussion thread, by creating a page and adding the following code at the top: {{#useliquidthreads:1}} (see for example this page)
  • Note that there is an Atom feed for each discussion page (left menu) you can subscribe to for getting updated with new replies. You can adjust your preferences (top right menu) for getting notified by email.


If you want to contribute to this wiki, contact me at fabien[dot]lagriffoul[at]oru[dot]se and I'll create an account for you.



Fabien Lagriffoul (Orebro University, Sweden.)
Neil T. Dantam (Colorado School of Mines, USA)
Caelan Garrett (Massachusetts Institute of Technology, USA)
Ali Akbari (Tech. U. of Catalonia, Spain)
Siddharth Srivastava (Arizona State University, USA)


This initiative is supported by the Swedish Knowledge Foundation (KKS) project Semantic Robots. It is also supported by NSF grants IIS 1317849 and CCF-1514372 to the Kavraki Lab at Rice University, USA.

RSS Workshops