Let's Push Things Forward: A Survey on Robot Pushing

Jochen Stüber, Claudio Zito*, Rustam Stolkin

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

78 Citations (Scopus)
1 Downloads (Pure)

Abstract

As robots make their way out of factories into human environments, outer space, and beyond, they require the skill to manipulate their environment in multifarious, unforeseeable circumstances. With this regard, pushing is an essential motion primitive that dramatically extends a robot's manipulation repertoire. In this work, we review the robotic pushing literature. While focusing on work concerned with predicting the motion of pushed objects, we also cover relevant applications of pushing for planning and control. Beginning with analytical approaches, under which we also subsume physics engines, we then proceed to discuss work on learning models from data. In doing so, we dedicate a separate section to deep learning approaches which have seen a recent upsurge in the literature. Concluding remarks and further research perspectives are given at the end of the paper.
Original languageEnglish
Article number8
JournalFrontiers in Robotics and AI
Volume7
DOIs
Publication statusPublished - 6 Feb 2020

Keywords

  • forward models
  • manipulation
  • motion prediction
  • pushing
  • robotics

ASJC Scopus subject areas

  • Computer Science Applications
  • Artificial Intelligence

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