Enhancing Path Planning Capabilities of Automated Guided Vehicles in Dynamic Environments: Multi-Objective PSO and Dynamic-Window Approach Article Swipe

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Thi-Kien Dao , Truong-Giang Ngo , Jeng‐Shyang Pan , Thi-Thanh-Tan Nguyen , Trong-The Nguyen ·

YOU? · · 2024 · Open Access · · DOI: https://doi.org/10.3390/biomimetics9010035

Automated guided vehicles (AGVs) are vital for optimizing the transport of material in modern industry. AGVs have been widely used in production, logistics, transportation, and commerce, enhancing productivity, lowering labor costs, improving energy efficiency, and ensuring safety. However, path planning for AGVs in complex and dynamic environments remains challenging due to the computation of obstacle avoidance and efficient transport. This study proposes a novel approach that combines multi-objective particle swarm optimization (MOPSO) and the dynamic-window approach (DWA) to enhance AGV path planning. Optimal AGV trajectories considering energy consumption, travel time, and collision avoidance were used to model the multi-objective functions for dealing with the outcome-feasible optimal solution. Empirical findings and results demonstrate the approach’s effectiveness and efficiency, highlighting its potential for improving AGV navigation in real-world scenarios.

Related Topics

Particle Swarm Optimization

Computer Science

The Obstacle Is The Way

Artificial Intelligence

Electrical Engineering

Concepts

Obstacle avoidance Particle swarm optimization Motion planning Computer science Computation Path (computing) Energy consumption Obstacle Collision avoidance Simulation Operations research Engineering Robot Mobile robot Collision Artificial intelligence Computer security Algorithm Machine learning Political science Programming language Law Electrical engineering

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Type: article
Language: en
Landing Page: https://doi.org/10.3390/biomimetics9010035
PDF: https://www.mdpi.com/2313-7673/9/1/35/pdf?version=1704435318
OA Status: gold
Cited By: 16
References: 60
Related Works: 10
OpenAlex ID: https://openalex.org/W4390615189

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OpenAlex ID: https://openalex.org/W4390615189

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DOI: https://doi.org/10.3390/biomimetics9010035

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Title: Enhancing Path Planning Capabilities of Automated Guided Vehicles in Dynamic Environments: Multi-Objective PSO and Dynamic-Window Approach

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Type: article

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Language: en

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Publication year: 2024

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Publication date: 2024-01-05

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Authors: Thi-Kien Dao, Truong-Giang Ngo, Jeng‐Shyang Pan, Thi-Thanh-Tan Nguyen, Trong-The Nguyen

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Landing page: https://doi.org/10.3390/biomimetics9010035

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Concepts: Obstacle avoidance, Particle swarm optimization, Motion planning, Computer science, Computation, Path (computing), Energy consumption, Obstacle, Collision avoidance, Simulation, Operations research, Engineering, Robot, Mobile robot, Collision, Artificial intelligence, Computer security, Algorithm, Machine learning, Political science, Programming language, Law, Electrical engineering

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Cited by: 16

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Citations by year (recent): 2025: 13, 2024: 3

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