Abstract
It is known that a behavior-based control approach is effective for acquiring an intelligent control system of robots. However, further improvements are required for making any behavior-based control system robust against changes in the environments. A module learning method has been applied in the framework of fuzzy behavior-based control to have an adaptive behavioral fusion. In this paper, an adaptive fusion strategy is proposed to adaptively select a cooperative fusion unit or competitive fusion unit, depending on the external sensor information. Some simulations are given to illustrate that the present control systems are flexible against the change of environments or untrained environments, compared to those with a conventional priority-based fusion unit.
| Original language | English |
|---|---|
| Pages (from-to) | 27-49 |
| Number of pages | 23 |
| Journal | Journal of Intelligent and Robotic Systems: Theory and Applications |
| Volume | 42 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Jan 1 2005 |
| Externally published | Yes |
Keywords
- Behavior-based control
- Behavioral fusion
- Fuzzy control
- Genetic algorithm
- Module learning
- Nonholonomic mobile robots
- Sensor information
ASJC Scopus subject areas
- Software
- Control and Systems Engineering
- Mechanical Engineering
- Industrial and Manufacturing Engineering
- Artificial Intelligence
- Electrical and Electronic Engineering