Path Planning Using Particle Swarm Optimization and Fuzzy Logic

Oultiligh, Ahmed; Ayad, Hassan; Elkari, Abdeljalil; Mjahed, Mostafa

doi:10.1007/978-3-030-51186-9_17

Cited by 2 publications

(2 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Table 1 presents an overview of these fuzzy rule bases. For instance, the entry at position (1,1) in Table 1 can be expressed as follows:…”

Section: It-2 Fuzzy Logic Controller For Goal-seekingmentioning

confidence: 99%

“…These include meta-heuristic methods, artificial intelligence techniques, fuzzy systems, and hybrid systems. In terms of meta-heuristic methodologies, the author [1] introduced a fusion of two distinct meta-heuristic approaches to enhance the trajectory optimization of a mobile robot. this fusion aims to ensure the robot's navigation in a partially known environment with static obstacles.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

IT-2 Fuzzy Control and Behavioral Approach Navigation System for Holonomic 4WD/4WS Agricultural Robot

Ait dahmad,

Ayad,

García Cerezo

et al. 2024

INT J COMPUT COMMUN, Int. J. Comput. Commun. Control

View full text Add to dashboard Cite

In contemporary agriculture, researchers are focusing on precision farming and environmentally conscious techniques, leading to the advancement of autonomous agricultural mobile robots. Consequently, A navigation system using TSK Interval Type-2 fuzzy logic has been developed and, for the first time, applied to a holonomic mobile agricultural robot equipped with four-wheel drive and steer. This system employs a behavioral approach to accomplish the robot’s primary objective in unfamiliar environments. It comprises four controllers: one exclusively dedicated to goal-seeking behavior, with the remaining controllers responsible for obstacle avoidance. Supervision of these controllers is conducted through the Mandani fuzzy logic approach, which combines the outputs of all four controllers, robot wheel velocities and steering angles, using a proposed equations. Various case studies were examined and simulated utilizing MATLAB and VREP software platform to assess the navigator system’s performance. The simulation outcomes showcase the efficiency of the proposed equations and the system’s navigation capabilities. The stability of the entire system was thoroughly examined and confirmed, employing the Lyapunov function, in environments with and without obstacles.

show abstract

“…Table 1 presents an overview of these fuzzy rule bases. For instance, the entry at position (1,1) in Table 1 can be expressed as follows:…”

Section: It-2 Fuzzy Logic Controller For Goal-seekingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

IT-2 Fuzzy Control and Behavioral Approach Navigation System for Holonomic 4WD/4WS Agricultural Robot

Ait dahmad,

Ayad,

García Cerezo

et al. 2024

INT J COMPUT COMMUN, Int. J. Comput. Commun. Control

View full text Add to dashboard Cite

show abstract

Genetic Programming to Optimize 3D Trajectories

Kotze,

Hildemann,

Santos

et al. 2024

IJGI

View full text Add to dashboard Cite

Trajectory optimization is a method of finding the optimal route connecting a start and end point. The suitability of a trajectory depends on not intersecting any obstacles, as well as predefined performance metrics. In the context of unmanned aerial vehicles (UAVs), the goal is to minimize the route cost, in terms of energy or time, while avoiding restricted flight zones. Artificial intelligence techniques, including evolutionary computation, have been applied to trajectory optimization with varying degrees of success. This work explores the use of genetic programming (GP) for 3D trajectory optimization by developing a novel GP algorithm to optimize trajectories in a 3D space by encoding 3D geographic trajectories as function trees. The effects of parameterization are also explored and discussed, demonstrating the advantages and drawbacks of custom parameter settings along with additional evolutionary computational techniques. The results demonstrate the effectiveness of the proposed algorithm, which outperforms existing methods in terms of speed, automaticity, and robustness, highlighting the potential for GP-based algorithms to be applied to other complex optimization problems in science and engineering.

show abstract

Path Planning Using Particle Swarm Optimization and Fuzzy Logic

Cited by 2 publications

References 18 publications

IT-2 Fuzzy Control and Behavioral Approach Navigation System for Holonomic 4WD/4WS Agricultural Robot

IT-2 Fuzzy Control and Behavioral Approach Navigation System for Holonomic 4WD/4WS Agricultural Robot

Genetic Programming to Optimize 3D Trajectories

Contact Info

Product

Resources

About