University of Illinois Urbana-Champaign

Feedback Particle Filter Algorithm for Simultaneous Localization and Map Building

Huang, Geng

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https://hdl.handle.net/2142/46493

Description

Title
Feedback Particle Filter Algorithm for Simultaneous Localization and Map Building
Author(s)
Huang, Geng
Contributor(s)
Mehta, Prashant G.
Issue Date
2012-05
Keyword(s)
  • robotics
  • robotic control
  • robot motion planning
  • simultaneous localization and map building
  • optimal control
  • particle filters
  • feedback particle filters
  • autonomous vehicle localization
Abstract
In this thesis, feedback-particle-filter-based algorithms to solve the simultaneous localization and map building (SLAM) problem are developed. Feedback particle filter is a new formulation of the particle filter for the nonlinear filtering problem based on the concepts from optimal control and mean-field game theory. A software package is also developed. The goal of SLAM is to compute the absolute location of a vehicle, starting from an unknown location in an unknown environment by incrementally building a map for the environment. Multiple landmarks are used to represent the environment. Based on measurements of relative positions between the landmarks and the vehicle, the absolute position of the vehicle is estimated simultaneously while localizing the landmarks.
Type of Resource
text
Language
en
Permalink
http://hdl.handle.net/2142/46493
Sponsor(s)/Grant Number(s)
  • National Science Foundation (NSF)
  • Air Force Office of Scientific Research (AFOSR)

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Senior Theses - Electrical and Computer Engineering PRIMARY
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