article

Adaptive behaviors of reactive mobile robot with Bayesian inference in nonstationary environments

Authors:

Hyeun-Jeong Min,

Sung-Bae ChoAuthors Info & Claims

Applied Intelligence, Volume 33, Issue 3

Pages 264 - 277

https://doi.org/10.1007/s10489-009-0164-0

Published: 01 December 2010 Publication History

Abstract

This paper presents a technique for a reactive mobile robot to adaptively behave in unforeseen and dynamic circumstances. A robot in nonstationary environments needs to infer how to adaptively behave to the changing environment. Behavior-based approach manages the interactions between the robot and its environment for generating behaviors, but in spite of its strengths of fast response, it has not been applied much to more complex problems for high-level behaviors. For that reason many researchers employ a behavior-based deliberative architecture. This paper proposes a 2-layer control architecture for generating adaptive behaviors to perceive and avoid moving obstacles as well as stationary obstacles. The first layer is to generate reflexive and autonomous behaviors with behavior network, and the second layer is to infer dynamic situations of the mobile robot with Bayesian network. These two levels facilitate a tight integration between high-level inference and low-level behaviors. Experimental results with various simulations and a real robot have shown that the robot reaches the goal points while avoiding stationary or moving obstacles with the proposed architecture.

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Cited By

Li CTian G(2020)Transferring the semantic constraints in human manipulation behaviors to robotsApplied Intelligence10.1007/s10489-019-01580-850:6(1711-1724)Online publication date: 10-Feb-2020
https://dl.acm.org/doi/10.1007/s10489-019-01580-8
Wu BZheng HFeng Y(2014)Point-based online value iteration algorithm in large POMDPApplied Intelligence10.1007/s10489-013-0479-840:3(546-555)Online publication date: 1-Apr-2014
https://dl.acm.org/doi/10.1007/s10489-013-0479-8

Index Terms

Adaptive behaviors of reactive mobile robot with Bayesian inference in nonstationary environments
1. Computer systems organization
  1. Embedded and cyber-physical systems
    1. Robotics
2. Computing methodologies
  1. Artificial intelligence

Index terms have been assigned to the content through auto-classification.

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Published In

cover image Applied Intelligence

Applied Intelligence Volume 33, Issue 3

December 2010

160 pages

ISSN:0924-669X

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Copyright © Copyright © 2010 Springer Science+Business Media, LLC.

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Kluwer Academic Publishers

United States

Publication History

Published: 01 December 2010

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Cited By

Li CTian G(2020)Transferring the semantic constraints in human manipulation behaviors to robotsApplied Intelligence10.1007/s10489-019-01580-850:6(1711-1724)Online publication date: 10-Feb-2020
https://dl.acm.org/doi/10.1007/s10489-019-01580-8
Wu BZheng HFeng Y(2014)Point-based online value iteration algorithm in large POMDPApplied Intelligence10.1007/s10489-013-0479-840:3(546-555)Online publication date: 1-Apr-2014
https://dl.acm.org/doi/10.1007/s10489-013-0479-8

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