Integrated Behavior-Based Control (iB2C) is a behavior-based control concept for developing robust and adaptive robotic systems. Complex autonomous functions are broken down into individual, interconnected behavioral modules that operate in parallel and can be coordinated based on the situation. This enables robots to respond flexibly to changes in their environment, tasks, and system states.

Architecture and Functionality

Behavioral networks consist of standardized modules with uniform interfaces. Three basic module types form the foundation:

• Behavior: Implements individual control and decision-making functions.
• Percept: Processes sensor data while taking its quality into account.
• Fusion: Combines information and outputs from various modules.

Complex functions can be organized hierarchically using Groups and Layers .

Behavior Coordination

The modules interact via four standardized meta-signals:

• Stimulation ( s): Initiation of a behavior.
• Inhibition ( i): Inhibition of a behavior.
• Activity ( a): Current influence of the behavior.
• Target Rating (r): Internally assessed readiness for activation.

Key Features

• Modularity: Reusable and extensible behavioral modules.
• Adaptability: Dynamic adaptation to changing situations
• Parallelism: Simultaneous execution of multiple behaviors.
• Robustness: Redundant functions and flexible behavioral coordination.
• Scalability: Hierarchical structuring of complex behavioral networks.

Applications in Robotics

Behavioral networks form the basis of self-adaptive robot architecture REACTiON. They enable the coordinated execution of perception, navigation, and safety functions, thereby supporting robust and situation-adaptive control of autonomous off-road robots.