Related Experiment Video
Updated: May 13, 2025
11:53
The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
Published on: October 14, 2017
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Simulation-based review of classical, heuristic, and metaheuristic path planning algorithms.
Kenneth Christopher Ugwoke1, Nwojo Agwu Nnanna2, Saleh El-Yakub Abdullahi2
1Department of Computer Science, Nile University of Nigeria, Plot 681, Cadastral Zone C, Airport Road, Jabi, Abuja Federal Capital Territory, Nigeria. kenchijoke@yahoo.com.
Scientific Reports
|April 12, 2025
Summary
This study categorizes key path-planning algorithms for autonomous robots, detailing their principles, applications, and challenges. A simulated comparison highlights algorithm performance for efficient robot navigation.
Area of Science:
- Robotics
- Artificial Intelligence
- Computer Science
Background:
- Path planning is crucial for autonomous robot navigation.
- It enables collision-free and efficient movement by selecting optimal routes.
- Effective path planning ensures successful robot operations in diverse environments.
Purpose of the Study:
- To introduce and categorize notable path-planning algorithms in robotics.
- To analyze the principles, features, challenges, and applications of these algorithms.
- To provide a comparative analysis of path-planning techniques through simulation.
Main Methods:
- Review and categorization of existing path-planning algorithms.
- In-depth analysis of algorithm principles, features, and challenges.
- Simulated comparison of selected path-planning algorithms.
Main Results:
- Categorization of prominent path-planning algorithms.
- Identification of strengths and weaknesses for each algorithm.
- Comparative performance data from simulated scenarios.
Conclusions:
- Path planning is fundamental for autonomous systems.
- Algorithm selection depends on specific operational requirements and environmental constraints.
- Future trends indicate advancements in dynamic and adaptive path-planning strategies.
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