Perception and Planning
{'Code': '05020000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'IIS', 'LongName': 'Div Of Information & Intelligent Systems'}}
{'SignBlockName': 'Joyce', 'PO_EMAI': None, 'PO_PHON': None}
The objective of this project is to study both logical and                  implementation aspects of sensor based robot planning.                              A Major goal of the project is to develop a formal model of                perception, knowledge, and planning, and a representation                       language defined over the model.  This formal theory will serve                 as a basis for the implementation of a domain independent                       planner.  The application of the theory to the planning of routes               through partially known territory will be studied.                                   For a robot to operate autonomously in a partially known                   world, it must be able to construct plans that rely on its                      gaining necessary information through its perceptions during the                execution of the plan. The proposed planner must understand the                 power and scope of its sensors. It must also understand how                     perceptions relate to the physical world, and how they increase                 the robot's knowledge.  It must be able to reason about                         plans that are only partially defined when first constructed, and               become gradually more elaborated during execution.
{'FirstName': 'Leora', 'LastName': 'Morgenstern', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Leora Morgenstern', 'EmailAddress': 'leora@watson.ibm.com', 'NSF_ID': '000188294', 'StartDate': '09/01/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'Brown University', 'CityName': 'PROVIDENCE', 'ZipCode': '029129100', 'PhoneNumber': '4018632777', 'StreetAddress': '1 PROSPECT ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Rhode Island', 'StateCode': 'RI', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'RI01', 'ORG_UEI_NUM': 'E3FDXZ6TBHW3', 'ORG_LGL_BUS_NAME': 'BROWN UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
{'Name': None, 'CityName': None, 'StateCode': None, 'ZipCode': None, 'StreetAddress': None, 'CountryCode': None, 'CountryName': None, 'StateName': None, 'CountryFlag': None, 'CONGRESSDISTRICT': None, 'CONGRESS_DISTRICT_PERF': '""'}
{'Code': '6840', 'Text': 'ROBOTICS'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1988&All=true', 'xml': '8801253.xml'}