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Related Experiment Video

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The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

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Path Following, Obstacle Detection and Obstacle Avoidance for Thrusted Underwater Snake Robots.

Eleni Kelasidi^1,2, Signe Moe^3,4, Kristin Y Pettersen¹

¹Department of Engineering Cybernetics, Centre for Autonomous Marine Operations and Systems, Norwegian University of Science and Technology, Trondheim, Norway.

Frontiers in Robotics and AI

|January 27, 2021

Summary

Underwater snake robots (USRs) navigate autonomously using a novel control system for path following and obstacle avoidance. This system enables efficient maneuvering and intervention capabilities for marine applications.

Keywords:

energy efficiency obstacle detection and avoidance path following thrusted USR underwater snake robots

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Area of Science:

Robotics
Marine Engineering
Bio-inspired Systems

Background:

Unmanned underwater vehicles (UUVs) are increasingly vital for oceanographic research and industry.
Underwater snake robots (USRs) offer enhanced maneuverability and intervention capabilities compared to traditional UUVs.
Energy-efficient propulsion and autonomous navigation are critical challenges for UUVs.

Purpose of the Study:

To develop and validate a control system for USR path following.
To implement algorithms for real-time obstacle detection and avoidance using computer vision.
To enhance the operational autonomy and efficiency of USRs in complex underwater environments.

Main Methods:

A USR equipped with tail thrusters and a head-mounted camera was utilized.
A computer vision algorithm processed camera data for obstacle detection and localization.
A control system used robot joints for directional control and tail thrusters for propulsion.
Obstacle circumvention involved following a circular path before rejoining the original trajectory.

Main Results:

The developed control system effectively enabled path following for the USR.
The obstacle detection and avoidance algorithms successfully guided the USR around detected obstacles.
Experimental results validated the proposed methods for autonomous navigation and maneuvering.

Conclusions:

The presented control system and algorithms enhance the autonomy and efficiency of USRs.
USRs equipped with this system can perform complex navigation and intervention tasks in underwater environments.
This research contributes to the advancement of bio-inspired underwater robotics.