Robot Manipulation in Open Environments: New Perspectives

Frank Guerin* (Corresponding Author), Paulo Abelha Ferreira

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


The problem of performing everyday manipulation tasks robustly in open environments is currently beyond the capabilities of artificially intelligent robots; humans are required. The difficulty arises from the high variability in open environments; it is not feasible to program for, or train for, every variation. This correspondence paper presents the case for a new approach to the problem, based on three mutually dependent ideas: 1) highly transferable manipulation skills; 2) choice of representation: a scene can be modeled in several different ways; 3) top-down processes by which the robot’s task can influence the bottom-up processes interpreting a scene. The approach we advocate is supported by evidence from what we know about humans, and also the approach is implicitly taken by human designers in designing representations for robots. We present brief results of an implementation of these ideas in robot vision, and give some guidelines for how the key ideas can be implemented more generally in practical robot systems.
Original languageEnglish
Pages (from-to)669-675
Number of pages7
JournalIEEE Transactions on Cognitive and Developmental Systems
Issue number3
Early online date5 Jun 2019
Publication statusPublished - 30 Sept 2020

Bibliographical note

The authors would like to thank useful ideas from the anonymous reviewers and P. Gajewski, S. Schmidt-Rohr, G. Bartels, A. Leonardis, and S. Ramamoorthy.


  • commonsense reasoning
  • robot manipulation
  • knowledge representation
  • Commonsense reasoning


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