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Local-Minimum-Free Artificial Potential Field Method for Obstacle Avoidance

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Intelligent Systems and Applications (IntelliSys 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 296))

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Abstract

In this paper we present a new formulation of the local minimum problem which characterizes the artificial potential field method for obstacle avoidance. Our approach consists of detecting the local-minimum situation by measuring the angle formed by the two force vectors (repulsive force and attractive force vectors). Afterward, we suggest adding a new vector expressed in term of the angle formed by two vectors. The modified APF method we are suggesting ensures a local minimum-free obstacle-free path planning algorithm. The developed algorithm is verified through MATLAB platform simulations. One robot is put in some position moves within a 50 × 50 m2 area to reach a goal point while avoiding three stationary obstacles. Four different initial configurations are simulated. The robot dynamics are represented by first-order integrator model. The obtained trajectories showed a clear effectiveness of the proposed algorithm.

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Author information

Authors and Affiliations

  1. LRPE Laboratory, University of Science and Technology Houari Boumediene (USTHB), BP 32 Alia, 16111, Algiers, Algeria

    Abbes Tahri & Lakhdar Guenfaf

Authors
  1. Abbes Tahri
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  2. Lakhdar Guenfaf
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Corresponding author

Correspondence to Lakhdar Guenfaf .

Editor information

Editors and Affiliations

  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

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Tahri, A., Guenfaf, L. (2022). Local-Minimum-Free Artificial Potential Field Method for Obstacle Avoidance. In: Arai, K. (eds) Intelligent Systems and Applications. IntelliSys 2021. Lecture Notes in Networks and Systems, vol 296. Springer, Cham. https://doi.org/10.1007/978-3-030-82199-9_20

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