Constructing relative spatial relationships of large-area objects using time-of-flight sensing and achieving...

Area of Science:

• Robotics
• Computer Vision
• 3D Imaging

Background:

• 3D scanning provides detailed object information but is often costly and inefficient for large-scale scenes.
• Existing methods struggle with meter-scale scanning, limiting applications for large objects or internal relational mapping.

Purpose of the Study:

• To develop an efficient method for constructing 3D point data of large-area objects using minimal sampling points.
• To demonstrate a novel approach for multi-dimensional wall flatness assessment based on relative object relationships.
• To explore potential applications in robotic construction.

Main Methods:

• Utilized a time-of-flight camera for point data acquisition.
• Applied the method to a wall surface for demonstration.
• Developed a technique to assess wall flatness using relative relationships from a single data acquisition.

Main Results:

• Successfully constructed 3D point data of a wall using a time-of-flight camera.
• Demonstrated a new method for multi-dimensional wall flatness assessment with a single scan.
• Showcased the potential for integrating this technique with robotic construction.

Conclusions:

• The proposed method offers an efficient alternative to traditional large-scale 3D scanning.
• Assessing wall flatness through relative relationships provides valuable data for construction applications.
• This technique has significant potential for enhancing robotic construction processes.