Semantic enhanced navigation among movable obstacles in the home environment

Nico Sun, Erfu Yang, Jonathan Corney, Yi Chen, Zeli Ma

Research output: Contribution to conferencePosterpeer-review

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An autonomous household robot has to be able to navigate through a variable environment and perform commonhousehold tasks. Additionally, in cluttered and narrow homes movement can become impossible unless obstacles are moved out of the way. Both challenges involve the manipulation of objects and a planning algorithm that can integrate the function of regions and objects to avoid the creation of new safety hazards during robot movement. We present a semantic detection method during path planning using a gridded semantic map to improve navigation among movable obstacles (NAMO) and support for simple household sub-tasks like cleaning a table and moving obstructing objects to another location. In our tests, the spatial planning was completed well within human reaction time, which is important for a natural interaction between a human and a robot.
Original languageEnglish
Number of pages4
Publication statusPublished - 24 Jan 2019
EventUK-RAS19 Conference - Loughborough University, Loughborough, United Kingdom
Duration: 24 Jan 201924 Jan 2019


ConferenceUK-RAS19 Conference
Country/TerritoryUnited Kingdom


  • planning
  • autonomous household robots
  • robotics
  • navigation among movable obstacles (NAMO)
  • semantic mapping


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