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Multi-Objective Optimization Robot Navigation Through a Graph-Driven PSO Mechanism

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Advances in Swarm Intelligence (ICSI 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13345))

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Abstract

In real-world robot applications such as service robots, mining mobile robots, and rescue robots, an autonomous mobile robot is required to visit multiple waypoints that it achieves multiple-objective optimizations. Such multiple-objective optimizations include robot travelling distance minimization, time minimization, turning minimization, etc. In this paper, a particle swarm optimization (PSO) algorithm incorporated with a Generalized Voronoi diagram (GVD) method is proposed for a robot to reach multiple waypoints with minimized total distance. Firstly, a GVD is used to form a Voronoi diagram in an obstacle populated environment to construct safety-conscious routes. Secondly, the sequence of multiple waypoints is created by the PSO algorithm to minimize the total travel cost. Thirdly, while the robot attempts to visit multiple waypoints, it traverses along the edges of the GVD to form a collision-free trajectory. The regional path locally from waypoints to nearest nodes or edges needs to be created to join the trajectory. A Node Selection Algorithm (NSA) is developed in this paper to implement such a protocol to build up regional path from waypoints to nearest nodes or edges on GVD. Finally, a histogram-based local reactive navigator is adopted for moving obstacle avoidance. Simulation and comparison studies validate the effectiveness and robustness of the proposed model.

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Author information

Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Mississippi State University, Mississippi State, MS, 39762, USA

    Timothy Sellers, Tingjun Lei & Chaomin Luo

  2. Department of Electrical Engineering, National Taipei University, and Tainan National University of the Arts, Tainan, Taiwan

    Gene Eu Jan

  3. Department of Robotics and Mechatronics Engineering, Kennesaw State University, Marietta, GA, 30060, USA

    Ying Wang

Authors
  1. Timothy Sellers
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  2. Tingjun Lei
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  3. Gene Eu Jan
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  4. Ying Wang
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  5. Chaomin Luo
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Corresponding author

Correspondence to Chaomin Luo .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Southern University of Science and Technology, Shenzhen, China

    Yuhui Shi

  3. Shenzhen University, Shenzhen, China

    Ben Niu

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Sellers, T., Lei, T., Jan, G.E., Wang, Y., Luo, C. (2022). Multi-Objective Optimization Robot Navigation Through a Graph-Driven PSO Mechanism. In: Tan, Y., Shi, Y., Niu, B. (eds) Advances in Swarm Intelligence. ICSI 2022. Lecture Notes in Computer Science, vol 13345. Springer, Cham. https://doi.org/10.1007/978-3-031-09726-3_7

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  • DOI: https://doi.org/10.1007/978-3-031-09726-3_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-09725-6

  • Online ISBN: 978-3-031-09726-3

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