2026-09-27T17:00:51Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/836322022-01-13T07:54:05Zcom_1721.1_7582com_1721.1_7581col_1721.1_131024
James H. Williams, Jr..
Singh, Mukul Kumar
Massachusetts Institute of Technology. Department of Mechanical Engineering.
Massachusetts Institute of Technology. Department of Mechanical Engineering
2014-01-09T18:54:27Z
2014-01-09T18:54:27Z
2013
http://hdl.handle.net/1721.1/83632
864715848
Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2013.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pag 23).
It is experimentally known that the flight lengths of random searches by foragers such as honey bees statistically belong to a power law distribution. Optimality of such random searches has been a topic of extensive research because knowing their optimal parameters may help applied sciences. Viswanathan et al. have shown the inverse-square power law to be the optimal law for such random searches. This thesis explores the capability of the model presented in such that it can be applied to Unmanned Autonomous Vehicles (UAVs). The thesis also identifies the minimum flight length, lmin, as an important factor that needs to be controlled based on the UAV's sensor range. We present a theoretical lmin as an explicit function of the sensor range, rv, and an estimated target density, p.
by Mukul Kumar Singh.
S.B.
29 pages
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by
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http://dspace.mit.edu/handle/1721.1/7582
Mechanical Engineering.
Evaluating levy flight parameters for random searches in a 2D space
Thesis
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<Abstract>It is experimentally known that the flight lengths of random searches by foragers such as honey bees statistically belong to a power law distribution. Optimality of such random searches has been a topic of extensive research because knowing their optimal parameters may help applied sciences. Viswanathan et al. have shown the inverse-square power law to be the optimal law for such random searches. This thesis explores the capability of the model presented in such that it can be applied to Unmanned Autonomous Vehicles (UAVs). The thesis also identifies the minimum flight length, lmin, as an important factor that needs to be controlled based on the UAV's sensor range. We present a theoretical lmin as an explicit function of the sensor range, rv, and an estimated target density, p.</Abstract>
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