Stereo vision-based fast obstacles avoidance without obstacles discrimination for indoor UAVs

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Abstract

A stereo vision-based obstacle awareness and avoidance algorithm for indoor UAVs is described in this paper. While in most papers UAVs perceive the environment by vision-based obstacle discrimination, in our method a scene depth map is directly used, which makes our algorithm more adaptive in complex environment with numerous obstacles. For the purpose of lower time cost and less match mistakes, edge information is used to improve original area-based stereo matching method. Furthermore, the perceived environment is represented by a grid-based depth map, according to which the optimal guide point is chosen. Finally, a feasible avoidance path is generated by adding way points while comparing the depth of hypothetic way points with the depth of corresponding grids. Experiments results show the effectiveness of our algorithm.

Original languageEnglish
Title of host publication2011 2nd International Conference on Artificial Intelligence, Management Science and Electronic Commerce, AIMSEC 2011 - Proceedings
Pages4332-4337
Number of pages6
DOIs
StatePublished - 2011
Event2011 2nd International Conference on Artificial Intelligence, Management Science and Electronic Commerce, AIMSEC 2011 - Zhengzhou, China
Duration: 8 Aug 201110 Aug 2011

Publication series

Name2011 2nd International Conference on Artificial Intelligence, Management Science and Electronic Commerce, AIMSEC 2011 - Proceedings

Conference

Conference2011 2nd International Conference on Artificial Intelligence, Management Science and Electronic Commerce, AIMSEC 2011
Country/TerritoryChina
CityZhengzhou
Period8/08/1110/08/11

Keywords

  • Area-based
  • Grid-based depth map
  • Obstacle avoidance
  • Stereo vision
  • Virtual destination
  • Way points

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