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Using Insect Electroantennogram Sensors on Autonomous Robots for Olfactory Searches

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A Nonlinear Observability Analysis of Ambient Wind Estimation with Uncalibrated Sensors, Inspired by Insect Neural

Floris van Breugel¹

¹University of Nevada, Reno, USA.

Proceedings of the ... IEEE Conference on Decision & Control. IEEE Conference on Decision & Control

|October 3, 2023

Summary

Estimating fluid flow direction is crucial for navigation. This study shows that robots and animals can self-calibrate sensors and estimate flow direction by changing course and integrating sensory data.

Keywords:

anemotaxis observability sensor calibration

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Area of Science:

Robotics and Biomechanics
Fluid Dynamics
Sensory Neuroscience

Background:

Estimating ambient fluid flow direction is vital for autonomous navigation in air and water.
Animals and robots rely on indirect measurements and active control for flow estimation.
Existing models suggest a 2D angular encoding of sensory information in insect brains.

Purpose of the Study:

To investigate the feasibility of self-calibration and flow direction estimation for mobile agents with changing sensor parameters.
To determine the necessary sensory inputs and maneuvers for continuous self-calibration and flow estimation.
To explore the potential link between self-calibration strategies and observed animal movement patterns.

Main Methods:

Nonlinear observability analysis applied to a dynamic system model.
Mathematical framework for fusing and temporally differentiating multiple sensory inputs.
Simulation of agent movement with varying course and orientation.

Main Results:

Continuous estimation of flow direction and self-calibration are mathematically feasible.
Effective self-calibration requires frequent changes in course and orientation.
Fusion and temporal differentiation of apparent flow, orientation, and motion data are essential.

Conclusions:

Mobile agents with angular sensors can achieve self-calibration and flow estimation.
Active changes in trajectory are key to overcoming sensor calibration drift.
Observed animal behaviors like zigzagging may be linked to flow estimation strategies.