| Autor: |
Melekhin, V. B., Khachumov, M. V. |
| Zdroj: |
Scientific & Technical Information Processing; Dec2022, Vol. 49 Issue 5, p333-340, 8p |
| Abstrakt: |
This article shows that usually the automatic control system of autonomous flying robots based on unmanned aerial vehicles has limited computing resources, which makes it impossible to use known labor-intensive logical models of knowledge representation and processing to plan goal-directed behavior. Thus, there is a need to develop a model of knowledge representation and processing that makes it possible to plan goal-oriented behavior under conditions of a priori uncertainty of the problem environment with polynomial complexity. To solve this problem, a model of knowledge representation is constructed in the form of a set of typical basic, intermediate, and terminal growth elements used to automatically plan goal-seeking behavior in the space of subtasks in the form of a growing reduction network model for solving complex problems under uncertainty. Automatic goal-setting procedures are developed that allow an autonomous flying robot to secure its activities under a priori uncertainty in an unstable problem environment. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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