Presidential Young Investigators Award:  Computational      Geometry/Optimization
{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}
{'SignBlockName': 'Radhakisan Baheti', 'PO_EMAI': None, 'PO_PHON': None}
Dr. Mitchell has been studying a variety of problems in computational           geometry that arise in robotics, computer-aided design, and computer            vision.  One problem of general interest is that of finding very                efficient algorithms for building shortest path maps and Voronoi                diagrams in two and three-dimensional obstacle spaces.  He has                  examined this problem with many different distance measures                     (Euclidean, link distance, "weighted regions", and others) and is               currently implementing some of these algorithms. Another major problem          area is that of computer vision, in which one desires a best fit                between a known object model and a given noisy image.  This leads to            questions of how to compute the "distance" between two arbitrary                shapes, where distance can have many different meanings and shapes can          be described in various ways (from point sets to arbitrary                      multiply-connected regions).                                                                                                                                    Many of his research problems have very simple visualizations. Imagine          a small mobile robot trying to get from point A (in the living room)            to point B (in the kitchen).  There are many obstacles in the way,              some of them known in advance (if, for instance, the robot is equipped          with a floorplan) and others unknown (such as the pet dog on the                floor).  The objective is to find a good path from A to B. This                 "shortest path problem" is fundamental in robotics, for if a robot is           to be automated to be able to plan tasks on its own, it must find               feasible paths (this is the "motion planning" problem) which, ideally,          are shortest according to some sense of optimality.
{'FirstName': 'Joseph S.', 'LastName': 'Mitchell', 'PI_MID_INIT': 'B', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Joseph S. B Mitchell', 'EmailAddress': 'joseph.mitchell@stonybrook.edu', 'NSF_ID': '000364690', 'StartDate': '11/01/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'Cornell University', 'CityName': 'ITHACA', 'ZipCode': '148502820', 'PhoneNumber': '6072555014', 'StreetAddress': '341 PINE TREE RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '19', 'CONGRESS_DISTRICT_ORG': 'NY19', 'ORG_UEI_NUM': 'G56PUALJ3KT5', 'ORG_LGL_BUS_NAME': 'CORNELL UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
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{'Code': '1518', 'Text': 'CONTROL, NETWORKS, & COMP INTE'}
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