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Lidar-Based Navigation of Subterranean Environments Using Bio-Inspired Wide-Field Integration of Nearness.

Michael T Ohradzansky¹, J Sean Humbert²

¹Department of Aerospace Engineering Sciences, University of Colorado Boulder, 3775 Discovery Drive, Boulder, CO 80303, USA.

Sensors (Basel, Switzerland)

|February 15, 2022

Summary

This study introduces a bio-inspired algorithm for efficient robot navigation in unknown subterranean environments. The method uses spatial inner-products to process depth data, enabling faster autonomous navigation for quadrotor platforms.

Keywords:

bio-inspired navigation quadrotor control sensorimotor convergence subterranean exploration

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Area of Science:

Robotics
Bio-inspired algorithms
Autonomous navigation

Background:

Robotic navigation in unknown environments faces challenges with high sensor data processing loads.
Efficiently processing depth measurements is crucial for fast and reliable navigation.

Purpose of the Study:

To present a bio-inspired algorithm for efficient processing of depth measurements.
To enable fast autonomous navigation in unknown subterranean environments using quadrotor platforms.

Main Methods:

Utilized a spatial inner-product to model bio-inspired sensorimotor convergence.
Extracted environmentally relative states from spatially distributed depth measurements using derived weighting functions.
Applied extracted states as feedback to control a simulated quadrotor platform.

Main Results:

Demonstrated autonomous navigation capabilities in simulated subterranean environments.
Successfully controlled a quadrotor platform using the developed algorithm.
Validated the algorithm in both generalized (infinite cylinder) and non-generalized (tunnels, caves) environments.

Conclusions:

The bio-inspired algorithm enables efficient depth data processing for rapid navigation.
The approach facilitates autonomous navigation in complex subterranean environments.
This method offers a promising solution for robotic exploration in unknown terrains.