Sampling-based algorithms for optimal motion planning

Article Properties
  • Language
    English
  • DOI (url)
    10.1177/0278364911406761
  • Publication Date
    2011/06/01
  • Journal
    The International Journal of Robotics Research
  • Indian UGC (Journal)
  • Refrences
    107
  • Citations
    1,511
  • Sertac Karaman Laboratory for Information and Decision Systems, Massachusetts Institute of Technology, Cambridge, MA, USA,
  • Emilio Frazzoli Laboratory for Information and Decision Systems, Massachusetts Institute of Technology, Cambridge, MA, USA
Abstract
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Karaman, Sertac, and Emilio Frazzoli. “Sampling-Based Algorithms for Optimal Motion Planning”. The International Journal of Robotics Research, vol. 30, no. 7, 2011, pp. 846-94, https://doi.org/10.1177/0278364911406761.
Karaman, S., & Frazzoli, E. (2011). Sampling-based algorithms for optimal motion planning. The International Journal of Robotics Research, 30(7), 846-894. https://doi.org/10.1177/0278364911406761
Karaman S, Frazzoli E. Sampling-based algorithms for optimal motion planning. The International Journal of Robotics Research. 2011;30(7):846-94.
Journal Categories
Technology
Electrical engineering
Electronics
Nuclear engineering
Electronics
Technology
Engineering (General)
Civil engineering (General)
Technology
Mechanical engineering and machinery
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Citations
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Citations Analysis
Category Category Repetition
Technology: Engineering (General). Civil engineering (General)818
Technology: Mechanical engineering and machinery696
Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics689
Science: Mathematics: Instruments and machines: Electronic computers. Computer science330
Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks282
The first research to cite this article was titled Autonomous golf ball picking robot design and development and was published in 2012. The most recent citation comes from a 2024 study titled Autonomous golf ball picking robot design and development . This article reached its peak citation in 2023 , with 259 citations.It has been cited in 337 different journals, 19% of which are open access. Among related journals, the IEEE Robotics and Automation Letters cited this research the most, with 137 citations. The chart below illustrates the annual citation trends for this article.
Citations used this article by year