Robot Path Planning: from Analytical to Computer Intelligence Approaches

In an era where robots are becoming an integral part of human quotidian activities, understanding how they function is crucial. Among the inherent building complexities, from electronics to mechanics, path planning emerges as a universal aspect of robotics. The primary contribution of this work is t...

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Vydáno v:Journal of intelligent & robotic systems Ročník 111; číslo 4; s. 112
Hlavní autoři: Dias, Pedro A., Carvalho de Souza, João Pedro, Solteiro Pires, E. J., Filipe, Vítor, Figueiredo, Daniel, Rocha, Luís F., Silva, Manuel F.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Dordrecht Springer Netherlands 14.10.2025
Springer Nature B.V
Témata:
Algorithms
Ant colony optimization
Artificial Intelligence
Collision avoidance
Control
Electrical Engineering
Energy consumption
Engineering
Genetic algorithms
Intelligence
Mechanical Engineering
Mechatronics
Neural networks
Particle swarm optimization
Path planning
Potential fields
Real time
Review Paper
Robot arms
Robot dynamics
Robotics
Robots
Analytical algorithms
Robot path planning
Computer intelligence algorithms
Robot manipulator
Mobile robots
ISSN:1573-0409, 0921-0296, 1573-0409
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Shrnutí:In an era where robots are becoming an integral part of human quotidian activities, understanding how they function is crucial. Among the inherent building complexities, from electronics to mechanics, path planning emerges as a universal aspect of robotics. The primary contribution of this work is to provide an overview of the current state of robot path planning topics and a comparison between those same algorithms and its inherent characteristics. The path planning concept relies on the process by which an algorithm determines a collision-free path between a start and an end point, optimizing parameters such as energy consumption and distance. The quest for the most effective path planning method has been a long-standing discussion, as the choice of method is highly dependent on the specific application. This review consolidates and elucidates the categories of path planning methods, specifically classical or analytical methods, and computer intelligence methods. In addition, the operational principles of these categories will be explored, discussing their respective advantages and disadvantages, and reinforcing these discussions with relevant studies in the field. This work will focus on the most prevalent and recognized methods within the robotics path planning problem, being mobile robotics or manipulator arms, including Cell Decomposition, A*, Probabilistic Roadmaps, Rapidly-exploring Random Trees, Genetic Algorithms, Particle Swarm Optimization, Ant Colony Optimization, Artificial Potential Fields, Fuzzy, and Neural Networks. Following the detailed explanation of these methods, a comparative analysis of their advantages and drawbacks is organized in a comprehensive table. This comparison will be based on various quality metrics, such as the type of trajectory provided (global or local), the scenario implementation type (real or simulated scenarios), testing environments (static or dynamic), hybrid implementation possibilities, real-time implementation, completeness of the method, consideration of the robot’s kinodynamic constraints, use of smoothing techniques, and whether the implementation is online or offline.
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ISSN:1573-0409
0921-0296
1573-0409
DOI:10.1007/s10846-025-02322-4