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Path Planning and Static Obstacle Avoidance for Unmanned Aerial Systems

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Advancements in Smart Computing and Information Security (ASCIS 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1760))

Abstract

The recent advent of computational intelligence and the field of deep learning has shown a significant application for the task of efficient navigation of automated and unmanned vehicles. The notion of a robot intelligently deciding a path based on minimalistic spatial knowledge and operating in a collision-free manner illustrates significant real-world importance. This paper offers a novel study for determining the best strategy for robust path planning in a simulated environment sufficed with static obstacles. The paradigm of behavior cloning and imitation learning is extensively explored, these techniques have depicted a better analogy to the human brain hence, justifying the experiments. This paper also conducts extensive tests on the existing technologies as baselines for an unbiased comparison, these algorithms include Rapidly- exploring Random Tree (RRT), A* search algorithm, and an improved rendition of the Ant Colony Optimization (ACO). The algorithms developed are centric to Unmanned Aerial Systems (UAS) however a correlation is also shown to unmanned ground systems and other automated robotics.

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Authors and Affiliations

  1. Institute of Technology, Nirma University, Ahmedabad, India

    Pranshav Gajjar, Virensinh Dodia, Siddharth Mandaliya & Vijay Ukani

  2. School of Technology, Pandit Deendayal Energy University, Gandhinagar, India

    Pooja Shah

  3. Department of Computer Engineering, Marwadi University, Gujarat, India

    Madhu Shukla

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  1. Pranshav Gajjar
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  2. Virensinh Dodia
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  3. Siddharth Mandaliya
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  4. Pooja Shah
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  5. Vijay Ukani
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  6. Madhu Shukla
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Corresponding author

Correspondence to Siddharth Mandaliya .

Editor information

Editors and Affiliations

  1. Marwadi University, Rajkot, India

    Sridaran Rajagopal

  2. AVPTI, Rajkot, India

    Parvez Faruki

  3. Marwadi University, Rajkot, India

    Kalpesh Popat

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Gajjar, P., Dodia, V., Mandaliya, S., Shah, P., Ukani, V., Shukla, M. (2022). Path Planning and Static Obstacle Avoidance for Unmanned Aerial Systems. In: Rajagopal, S., Faruki, P., Popat, K. (eds) Advancements in Smart Computing and Information Security. ASCIS 2022. Communications in Computer and Information Science, vol 1760. Springer, Cham. https://doi.org/10.1007/978-3-031-23095-0_19

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  • DOI: https://doi.org/10.1007/978-3-031-23095-0_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-23094-3

  • Online ISBN: 978-3-031-23095-0

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