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Environment Mapping Using Sensor Fusion of 2D Laser Scanner and 3D Ultrasonic Sensor for a Real Mobile Robot.

Tien Quang Tran¹, Andreas Becker¹, Damian Grzechca²

¹Faculty of Information Technology, Dortmund University of Applied Science and Arts, Sonnenstr. 96, 44139 Dortmund, Germany.

Sensors (Basel, Switzerland)

|June 2, 2021

Summary

This study introduces a sensor fusion framework combining 2D LIDAR and 3D ultrasonic sensors for detailed 3D environment mapping. This approach enhances robot perception and localization while reducing resource requirements for lightweight robots.

Keywords:

2D/3D map 3D ultrasonic sensor LiDAR mapping sensor fusion

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Area of Science:

Robotics
Sensor Fusion
Environmental Mapping

Background:

Accurate environmental mapping is crucial for robot navigation, planning, and manipulation.
Existing 3D mapping solutions often rely on expensive 3D LiDAR or complex visual processing.

Purpose of the Study:

To develop a cost-effective 3D mapping framework using sensor fusion.
To enhance environmental perception and ego-pose estimation for robots with limited resources.

Main Methods:

A data-in-decision-out fusion framework integrating 2D LIDAR and 3D ultrasonic sensors.
Development of sensor models for map updating and discussion of 2D/3D map representations.
Comparison of various probabilistic fusion methods and selection criteria.

Main Results:

The proposed fusion approach successfully generated detailed 2D and 3D maps of indoor environments.
Sensor fusion improved environmental estimation and ego-pose accuracy compared to individual sensors.
The system demonstrated enhanced robot perception with a low-cost 3D ultrasonic sensor.

Conclusions:

The fusion framework offers a resource-efficient method for detailed 3D environment mapping.
This approach is particularly beneficial for robust, lightweight robots with constrained computational power.
Sensor fusion significantly enhances a robot's understanding of its surroundings.