Least square sparse mapping and octree-based A* algorithm

Toshinobu Watanabe, Emre Balci, Eric N. Johnson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper describes an architecture designed to enable to detect an obstacle by monoc- ular camera and create a path to avoid it. This technique consists of three parts: prefilter, occupied grid map, and octree-based A* algorithm. The prefilter includes initialization and update. As the initialization, four methods: Linear Least Square, inhomogeneous Singular Value Decomposition (SVD), homogeneous SVD, and nonlinear optimization, are compared. The recursive least square techinique is used for the update of the feature point position. This result is connected with the octree-based occupancy grid map. Finally, we inform the new A* algorithm based on the octree data structure.

Original languageEnglish (US)
Title of host publicationAIAA Information Systems-AIAA Infotech at Aerospace
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
Edition209989
ISBN (Print)9781624105272
DOIs
Publication statusPublished - Jan 1 2018
EventAIAA Information Systems-AIAA Infotech at Aerospace, 2018 - Kissimmee, United States
Duration: Jan 8 2018Jan 12 2018

Publication series

NameAIAA Information Systems-AIAA Infotech at Aerospace, 2018
Number209989

Other

OtherAIAA Information Systems-AIAA Infotech at Aerospace, 2018
CountryUnited States
CityKissimmee
Period1/8/181/12/18

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All Science Journal Classification (ASJC) codes

  • Aerospace Engineering
  • Industrial and Manufacturing Engineering

Cite this

Watanabe, T., Balci, E., & Johnson, E. N. (2018). Least square sparse mapping and octree-based A* algorithm. In AIAA Information Systems-AIAA Infotech at Aerospace (209989 ed.). (AIAA Information Systems-AIAA Infotech at Aerospace, 2018; No. 209989). American Institute of Aeronautics and Astronautics Inc, AIAA. https://doi.org/10.2514/6.2018-2013