Hidden Markov Model for Dynamic Obstacle Avoidance of Mobile Robot Navigation

Research output: Contribution to journalArticle

91 Citations (Scopus)

Abstract

Models and control strategies for dynamic obstacle avoidance in visual guidance of mobile robot are presented. Characteristics that distinguish the visual computation and motion-control requirements in dynamic environments from that in static environments are discussed. Objectives of the vision and motion planning are formulated as: 1) finding a collision-free trajectory that takes account of any possible motions of obstacles in the local environment; 2) such a trajectory should be consistent with a global goal or plan of the motion; and 3) the robot should move at as high a speed as possible, subject to its kinematic constraints. A stochastic motion-control algorithm based on a hidden Markov model (HMM) is developed. Obstacle motion prediction applies a probabilistic evaluation scheme. Motion planning of the robot implements a trajectory-guided parallel-search strategy in accordance with the obstacle motion prediction models. The approach simplifies the control process of robot motion.

Original languageEnglish (US)
Pages (from-to)390-397
Number of pages8
JournalIEEE Transactions on Robotics and Automation
Volume7
Issue number3
DOIs
StatePublished - Jul 1991

Fingerprint

Collision avoidance
Hidden Markov models
Mobile robots
Navigation
Trajectories
Robots
Motion control
Motion planning
Kinematics

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

Hidden Markov Model for Dynamic Obstacle Avoidance of Mobile Robot Navigation. / Zhu, Qiuming.

In: IEEE Transactions on Robotics and Automation, Vol. 7, No. 3, 07.1991, p. 390-397.

Research output: Contribution to journalArticle

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