Hybrid and Multi-controller Architecture for Autonomous System - Application to the Navigation of a Mobile Robot

Azzabi, Amani; Regaieg, Marwa; Adouane, Lounis; Nasri, Othman

doi:10.5220/0005065404910497

Cited by 2 publications

(2 citation statements)

References 11 publications

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“…This not only enhances the obstacle-avoidance capabilities of UAVs, but also serves to minimize flight costs to meet the practical requirements of agricultural tasks, considering multiple factors such as flight efficiency, obstacle avoidance, safety, and traffic laws [3]. The problem of path planning is inherently intricate, so it needs to be solved with a combination of mathematical modeling and computer algorithms [4]. With increasing mission complexity in dynamic, changing environments, UAV path planning must employ real-time, high-performance, and diversified approaches to ensure the safe and efficient completion of UAV flight missions [5].…”

Section: Introductionmentioning

confidence: 99%

A UAV Path Planning Method in Three-Dimensional Space Based on a Hybrid Gray Wolf Optimization Algorithm

Feng,

Sun,

Zhang

et al. 2023

Electronics

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Path planning, which is needed to obtain collision-free optimal paths in complex environments, is one key step within unmanned aerial vehicle (UAV) systems with various applications, such as agricultural production, target tracking, and environmental monitoring. A new hybrid gray wolf optimization algorithm—SSGWO—is proposed to plan paths for UAVs under three-dimensional agricultural environments in this paper. A nonlinear convergence factor based on trigonometric functions is used to balance local search and global search. A new relative-distance fitness adaptation strategy is created to increase the convergence speed of the SSGWO. Integrating the simulated annealing (SA) algorithm, an alternative position update strategy based on SA is proposed to improve the search process with diverse capabilities. Finally, a B-spline curve is introduced into a smooth path to ensure the path’s feasibility. The simulation results show that the SSGWO algorithm has better convergence accuracy and stability, and can obtain higher-quality paths in a three-dimensional environment, compared with GWO, MGWO, IGWO, and SOGWO.

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Section: Introductionmentioning

confidence: 99%

A UAV Path Planning Method in Three-Dimensional Space Based on a Hybrid Gray Wolf Optimization Algorithm

Feng,

Sun,

Zhang

et al. 2023

Electronics

View full text Add to dashboard Cite

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“…It aims to find a safe collision-free path from the start position to the goal while avoiding obstacles (Babinec et al, 2018; Hachour, 2008; Hong et al, 2011; Jiang et al, 2015). Path planning can be divided into global path planning based on a known environment and local path planning based on sensor information (Azzabi and Nouri, 2017; Azzabi et al, 2014). One of the best-known local path planning algorithms is the artificial potential field (APF).…”

Section: Introductionmentioning

confidence: 99%

An advanced potential field method proposed for mobile robot path planning

Azzabi

Nouri

2019

Transactions of the Institute of Measurement and Control

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In this paper, both the local minimum and the goal non-reachable with obstacles nearby (GNRON) problems have been solved on the artificial potential field (APF) for mobile robot path planning in a bounded environment. The GNRON problem occurs when the goal’s position is inside the circle of influence of the obstacle. This phenomenon gives rise to a larger repulsive force with regard to the attractive force. Therefore, a stronger attractive function is proposed to ensure that the robot reaches the target successfully. The local minimum problem occurs when the robot, the goal and the centre of the obstacle are aligned. This situation engenders a total potential force equal to zero before reaching the goal position. To overcome this problem, a novel of repulsive potential function is proposed by activating a virtual escaping force when a local minimum is detected. This force behaves as a rotational force allowing the robot to escape from the deadlock positions and turn smoothly away from obstacles in the direction of the target. The combination of the new attractive force and the novel repulsive force could solve the local minimum and the GNRON problems. Finally, some methodic simulations, based on a comparative study with other methods from the literature, are carried out to validate and demonstrate the effectiveness of the advanced potential field method to handle the local minimum and GNRON problems.

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Hybrid and Multi-controller Architecture for Autonomous System - Application to the Navigation of a Mobile Robot

Cited by 2 publications

References 11 publications

A UAV Path Planning Method in Three-Dimensional Space Based on a Hybrid Gray Wolf Optimization Algorithm

A UAV Path Planning Method in Three-Dimensional Space Based on a Hybrid Gray Wolf Optimization Algorithm

An advanced potential field method proposed for mobile robot path planning

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