Vision-based obstacle avoidance of wheeled robots using fast estimation

A. Dippold, L. Ma, N. Hovakimyan

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


This paper discusses vision-based static obstacle avoidance for nonholonomic robots. The robot is equipped with an inertial measurement unit that provides measurements of the vehicle's position and velocity, and a monocular camera that detects the obstacles. The obstacle avoidance algorithm deforms the vehicle's original path around isolated obstacles in a direction that minimizes a given potential function. This potential function is defined such that larger distances between the vehicle and obstacles yield lower values. Two estimation schemes are applied for the estimation task. The first is an existing method known in the literature as identifer-based observer that provides exponential convergence rate for the resulting error dynamics. The second is a recently-developed fast estimator that provides estimates of the unknown parameters with quantifiable bounds. It is shown that the performance of the fast estimator and its effect on the obstacle avoidance algorithm can be arbitrarily improved by appropriate choice of parameters as compared to the identifier-based observer method. Simulation results illustrate the theoretical findings.

Original languageEnglish (US)
Title of host publicationAIAA Guidance, Navigation and Control Conference and Exhibit
PublisherAmerican Institute of Aeronautics and Astronautics Inc.
ISBN (Print)9781563479458
StatePublished - 2008

Publication series

NameAIAA Guidance, Navigation and Control Conference and Exhibit

ASJC Scopus subject areas

  • Aerospace Engineering
  • Control and Systems Engineering


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