Integrated guidance navigation and control for a fully autonomous indoor UAS

  • Girish Chowdhary
  • , D. Michael Sobers
  • , Chintasid Pravitra
  • , Claus Christmann
  • , Allen Wu
  • , Hiroyuki Hashimoto
  • , Chester Ong
  • , Roshan Kalghatgi
  • , Eric Johnson

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

Abstract

This paper describes the details of a Quadrotor miniature unmanned aerial system capable of autonomously exploring cluttered indoor areas without relying on any external navigational aids such as GPS. A streamlined Simultaneous Localization and Mapping (SLAM) algorithm is implemented onboard the vehicle to fuse information from a scanning laser range sensor, an inertial measurement unit, and an altitude sonar to provide relative position, velocity, and attitude information. This state information, with a self-generated map, is used to implement a frontier-based exhaustive search of an indoor environment. To ensure the SLAM algorithm has sufficient information to form a reliable solution, the guidance algorithm ensures the vehicle approaches frontier waypoints through a path that remains within sensor range of indoor structures. Along with a detailed description of the system, simulation and hardware testing results are presented.

Original languageEnglish (US)
Title of host publicationAIAA Guidance, Navigation, and Control Conference 2011
StatePublished - Dec 1 2011
EventAIAA Guidance, Navigation and Control Conference 2011 - Portland, OR, United States
Duration: Aug 8 2011Aug 11 2011

Other

OtherAIAA Guidance, Navigation and Control Conference 2011
Country/TerritoryUnited States
CityPortland, OR
Period8/8/118/11/11

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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