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Variable Speed Robot Navigation by an ACO Approach

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Book cover Advances in Swarm Intelligence (ICSI 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11655))

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Abstract

A variable-speed-based navigation and map building method of an autonomous mobile robot is developed in this paper in cooperation with an ant colony optimization algorithm (ACO). In real-world applications, an autonomous mobile robot is expected to operate at variable speed. It should slow down in vicinity of obstacles, whereas moving at high speed in open areas. A LIDAR-based local navigator algorithm integrated with a variable speed module is implemented for local navigation and obstacle avoidance. A variable speed navigation paradigm is developed in integration with the ACO algorithm to dynamically adapt its speed to the environment scenarios. In addition to the variable speed ACO based navigation, grid-based map representations are imposed for real-time autonomous robot navigation. Simulation and comparison studies demonstrate effectiveness of the proposed real-time variable-speed-based ACO approach of an autonomous mobile robot.

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Authors and Affiliations

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

    Tingjun Lei & Chaomin Luo

  2. Graduate Institute of Animation and Film Art, Tainan National University of the Arts, Tainan, Taiwan

    Gene Eu Jan

  3. Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu, Taiwan

    Kevin Fung

Authors
  1. Tingjun Lei
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  2. Chaomin Luo
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  3. Gene Eu Jan
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  4. Kevin Fung
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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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Lei, T., Luo, C., Jan, G.E., Fung, K. (2019). Variable Speed Robot Navigation by an ACO Approach. In: Tan, Y., Shi, Y., Niu, B. (eds) Advances in Swarm Intelligence. ICSI 2019. Lecture Notes in Computer Science(), vol 11655. Springer, Cham. https://doi.org/10.1007/978-3-030-26369-0_22

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  • DOI: https://doi.org/10.1007/978-3-030-26369-0_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-26368-3

  • Online ISBN: 978-3-030-26369-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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