Abstract
In order to successfully perform a task, a situated system requires some information about its domain. If we can understand what information the system requires, we may be able to equip it with more suitable sensors or make better use of the information available to it. These considerations have motivated roboticists to examine the issue of sensor design, and in particular, the minimal information required to perform a task. We show here that reasoning in terms of what the robot knows and needs to know to perform a task is a useful approach for analyzing these issues. We extend the formal framework for reasoning about knowledge, already used in AI and distributed computing, by developing a set of basic concepts and tools for modeling and analyzing the knowledge requirements of tasks. We investigate properties of the resulting framework, and show how it can be applied to robotics tasks.
Original language | English |
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Pages (from-to) | 317-349 |
Number of pages | 33 |
Journal | Artificial Intelligence |
Volume | 98 |
Issue number | 1-2 |
DOIs | |
State | Published - 1 Jan 1998 |
Keywords
- (Skeletal) knowledge-based programs
- Configuration space
- Knowledge
- Knowledge capability
- Knowledge complexity
- Manipulation tasks
- Sensor design
ASJC Scopus subject areas
- Language and Linguistics
- Linguistics and Language
- Artificial Intelligence