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Updated: Dec 28, 2025

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

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

Published on: October 14, 2017

Autonomous Dam Surveillance Robot System Based on Multi-Sensor Fusion.

Chao Zhang¹, Quanzhong Zhan¹, Qi Wang²

¹Information Center of the Ministry of water resources of the P.R.C, Beijing 100053, China.

Sensors (Basel, Switzerland)

|February 22, 2020

Summary

Autonomous robots enhance dam safety surveillance. This system uses sensors and AI for real-time crack detection and navigation, improving operational stability and reducing human risk in complex environments.

Keywords:

autonomous navigation dam surveillance fusion localization water conversancy robot

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Area of Science:

Engineering
Robotics
Artificial Intelligence

Background:

Dams are critical infrastructure requiring continuous safety monitoring.
Traditional dam surveillance is labor-intensive and potentially hazardous.
Complex dam environments necessitate advanced monitoring solutions.

Purpose of the Study:

To design an autonomous robot system for dam ground surveillance.
To enhance dam safety and operational stability through robotic monitoring.
To develop a practical and robust system for real-time dam inspection.

Main Methods:

Development of a skid-steered mobile robot platform with MCU and IMU control.
Integration of a low-cost LiDAR for odometry estimation.
Implementation of a dual Kalman filter loop fusing wheel encoder, IMU, LiDAR odometry, and GNSS data for robust localization.
Deployment of a YOLO v3 network for real-time crack and human detection.
Utilization of IoT technology for system connectivity.

Main Results:

A functional autonomous robot platform for dam surveillance was created.
The sensor fusion and Kalman filter approach yielded robust localization.
The YOLO v3 network achieved real-time recognition of cracks and people.
The integrated system demonstrated practicality and robustness.

Conclusions:

The proposed autonomous robot system offers a viable solution for dam ground surveillance.
The system enhances safety by reducing human exposure to hazardous environments.
Real-time data acquisition and analysis improve dam integrity monitoring and maintenance.