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Improving Dynamic Navigation Algorithms

Yue, Weiya, Ph.D.
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1368028468

Abstract Details

2013, PhD, University of Cincinnati, Engineering and Applied Science: Computer Science and Engineering.
Navigation algorithms for advanced autonomous vehicles, such as an unmanned automobile or airplane, require improved response times to complete numerous tasks that are still only imagined. Existing navigation algorithms tend to be incremental, do not take full advantage of accumulated information to compute a next move, and tend to be too eager in recomputing much information when a new optimal path must be found. The result is unnecessary per-round state recalculations that slow the algorithms considerably. The formalization of a general framework for dynamic planning algorithms, aimed at eliminating such recalculations by considering the relationship between optimal solutions between rounds, is proposed. The framework is based on our successful work which improved the speed of the well-known D*lite algorithm by up to eight times. The expected direct result of this research is to improve the performance of navigation algorithms in various terrains. As an example, the framework is applied to the Anytime D* algorithm, a variant of D*Lite, to get a new algorithm, called IAD*, which is an order of magnitude faster than Anytime D*. Moreover, the IAD* algorithm and the AWA* algorithm are combined to form another Anytime variant, and another new dynamic anytime algorithm, called DAWA*, the first dynamic anytime algorithm able to utilize time resource continuously. These improvements show the extensibility and robustness of the proposed framework.
John Franco, Ph.D. (Committee Chair)
Raj Bhatnagar, Ph.D. (Committee Member)
Yizong Cheng, Ph.D. (Committee Member)
Wen Ben Jone, Ph.D. (Committee Member)
John Schlipf, Ph.D. (Committee Member)
104 p.
Computer Science
planning; dynamic navigation; ID Lite algorithm; anytime algorithm;

Recommended Citations

Citations

  • Yue, W. (2013). Improving Dynamic Navigation Algorithms [Doctoral dissertation, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1368028468

    APA Style (7th edition)

  • Yue, Weiya. Improving Dynamic Navigation Algorithms. 2013. University of Cincinnati, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1368028468.

    MLA Style (8th edition)

  • Yue, Weiya. "Improving Dynamic Navigation Algorithms." Doctoral dissertation, University of Cincinnati, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1368028468

    Chicago Manual of Style (17th edition)

ucin1368028468
426
© 2013, all rights reserved.
This open access ETD is published by University of Cincinnati and OhioLINK.