The DOI matches its Crossref record; 124 of the 124 references it cites were found in a registry or an index.
Path Planning for Autonomous Mobile Robots: A Review
Open accessAbstract
Providing mobile robots with autonomous capabilities is advantageous. It allows one to dispense with the intervention of human operators, which may prove beneficial in economic and safety terms. Autonomy requires, in most cases, the use of path planners that enable the robot to deliberate about how to move from its location at one moment to another. Looking for the most appropriate path planning algorithm according to the requirements imposed by users can be challenging, given the overwhelming number of approaches that exist in the literature. Moreover, the past review works analyzed here cover only some of these approaches, missing important ones. For this reason, our paper aims to serve as a starting point for a clear and comprehensive overview of the research to date. It introduces a global classification of path planning algorithms, with a focus on those approaches used along with autonomous ground vehicles, but is also extendable to other robots moving on surfaces, such as autonomous boats. Moreover, the models used to represent the environment, together with the robot mobility and dynamics, are also addressed from the perspective of path planning. Each of the path planning categories presented in the classification is disclosed and analyzed, and a discussion about their applicability is added at the end.
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Cites
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MethodSampling-based algorithms for optimal motion planning
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Cited by
A Comprehensive Review of Path-Planning Algorithms for Planetary Rover Exploration
Miao, Q., & Wei, G. (2025) · Remote Sensing · doi:10.3390/rs17111924 · Cited by 13
Metadata
- Authors
- Sánchez-Ibáñez, J. R., Pérez-del-Pulgar, C. J., & García-Cerezo, A.
- Venue
- Sensors
- Publisher
- MDPI AG
- Published
- 2021-11-26
- Volume
- 21
- Issue
- 23
- Pages
- 7898
- ISSN
- 1424-8220 (ISSN-L)
- OpenAlex
- W3217170181
- Cited by
- 462
- References
- 124
- FWCI
- 20.64
- Type
- journal article
- Language
- en
- Open access
- gold
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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