2026-09-19T06:48:00Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/29605 2023-07-10 col_2142_5131 col_2142_8888 com_2142_5130 com_2142_8887 com_2142_234

Hutchinson, Seth A. Bonnie, Devin A. 2012-02-06T20:06:21Z 2012-02-06T20:06:21Z 2012-02-06T20:06:21Z 2011-12 This thesis considers the problem of modeling search for a single, non-moving target in a continuous environment, where the search agent's only observations are obtained from a binary sensor. To model this problem, the widely used Bayesian filtering approach is employed to obtain the general filtering equations for the posterior distribution representing the object's location over the workspace. Given a likelihood and prior belief belonging to the exponential family class, while using this class's self-conjugacy property, an exact, finite representation of the object posterior is explicitly derived. Though complexity issues may render this exact representation infeasible for computation, regularized particle filtering is utilized to yield a continuous approximation of the object belief. To demonstrate the validity of the search model, a gradient-ascent search strategy is applied with care taken to avoid local maxima. This is done with multiple simulations for various prior distributions. Finally, future work is described for search applications and approximation schemas relevant to the structure of the search model presented. Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2011-08-02T21:50:12Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 1 Bonnie_Devin.pdf: 3055853 bytes, checksum: eda2812efd42b71276032b39c2db217c (MD5) Made available in DSpace on 2012-02-06T20:06:21Z (GMT). No. of bitstreams: 2 Bonnie_Devin.pdf: 3055849 bytes, checksum: 0a40ffcd526335c3fb1888758bb348f5 (MD5) license.txt: 4061 bytes, checksum: d83fe6a1a52bb1524830a795d682086f (MD5) http://hdl.handle.net/2142/29605 en Copyright 2011 Devin A. Bonnie Bayesian Search single robot search multi robot search atypical exponential family mixture belief self conjugacy binary sensor search Probabilistic search: a Bayesian approach in a continuous workspace Electrical & Computer Eng 1933 Electrical & Computer Engr 1200 University of Illinois at Urbana-Champaign Thesis M.S. MS:Electr & Computer Eng-UIUC 10KS1200MS