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Cited by 170Robotic Path Planning AlgorithmsMetaheuristic Optimization Algorithms ResearchAdvanced Manufacturing and Logistics Optimization

Task allocation and collision-free path planning of centralized multi-robots system for industrial plant inspection using heuristic methods

Jose, Kelin, Pratihar, Dilip Kumar·2016·Robotics and Autonomous Systems
DOI 10.1016/j.robot.2016.02.003
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Crossref · 10.1016/j.robot.2016.02.003

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  • Robotic navigation aims to achieve accurate positioning and avoid obstacles in the pathway, satisfying constraints such as limited operating space, distance, energy, and time.

    “The process known as robotic navigation aims to achieve accurate positioning and avoiding obstacles in the pathway.It is essential to satisfy constraints such as limited operating space, distance, energy, and time [78].”

    From Advanced Applications of Industrial Robotics: New Trends and Possibilities (2021) · cites this paper as [78]

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Authors
Jose, K., & Pratihar, D. K.
Affiliations
Indian Institute of Technology Kharagpur (IN)
Corresponding author
Pratihar, Dilip Kumar
ORCID
Venue
Robotics and Autonomous Systems
Publisher
Elsevier BV
Published
2016-06
Volume
80
Pages
34-42
ISSN
0921-8890 (ISSN-L)
DOI
10.1016/j.robot.2016.02.003
OpenAlex
W2293302471
Cited by
170
References
0
Citations by year
2026: 7 · 2025: 28 · 2024: 21 · 2023: 14 · 2022: 15 · 2021: 27 · 2020: 24 · 2019: 12 · 2018: 11 · 2017: 10 · 2016: 1
FWCI
6.84
Type
journal article
Language
en
Open access
closed
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations
Robotics and Autonomous Systems (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Robotic Path Planning Algorithms
  • Physical Sciences › Computer Science › Artificial Intelligence › Metaheuristic Optimization Algorithms Research
  • Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Advanced Manufacturing and Logistics Optimization
Keywords
multi-robot systems, task allocation, collision-free path planning, collision avoidance, genetic algorithm, A* algorithm, centralized control, heuristic scheduling, task completion time

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