Active Sensing Subserves Task-Level Control

Area of Science:

• Robotics and Control Theory
• Animal Behavior and Biomechanics
• Sensor Fusion and Adaptive Systems

Background:

• Active sensing traditionally involves energy expenditure for information gathering.
• Existing engineered systems often prioritize speed and precision over biological robustness.
• Biological systems exhibit sophisticated active sensing behaviors unmatched by current robotics.

Purpose of the Study:

• To propose that active sensing movements emerge from the interplay of adaptive sensors, movement-sensing linkage, and task-level control.
• To challenge the notion that active sensing is solely driven by sensory goals like uncertainty reduction.
• To highlight the potential of biological active sensing strategies for improving robotic sensing and control.

Main Methods:

• Integration of empirical data from biological organisms.
• Application of mathematical control theory to model active sensing.
• Analysis of behavioral modes (explore/exploit) in biological systems.

Main Results:

• Active sensing is fundamentally subservient to task-level control, not sensory goals.
• Biological active sensing involves discrete epochs of 'explore' and 'exploit' behavioral modes.
• This biological control strategy, utilizing adaptive sensors and mode switching, is underutilized in engineered systems.

Conclusions:

• Active sensing is a control-driven phenomenon essential for robust biological behaviors.
• Understanding biological active sensing and mode switching can significantly advance robotic capabilities.
• Control theory provides a framework for bridging the gap between biological and engineered systems.