Mobile Scanning System Pose Compensation for 3D Map Registration
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Solution Overview
Problem
Existing environment scanning systems face challenges in automatic registration of 3D scans, requiring manual intervention and resulting in inefficiencies, incomplete scans, and increased costs due to the need for manual registration processes, which can be time-consuming and impractical in certain scenarios.
Innovation Solution
A mobile scanning system integrated with an automated transporter robot that captures scan-data while moving, using a method involving anchor scans and compensation vectors to register and generate accurate maps of the environment, allowing for simultaneous localization and mapping (SLAM) without relying solely on sensor data fusion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual registration processes are used to register 3D scans, then registration accuracy can be maintained, but time consumption and operational complexity increase significantly
Solution Approach 1:
The system performs automatic registration using onboard sensors (IMU, wheel encoders) to self-determine pose changes between scans, eliminating the need for manual registration operations. The transporter robot independently computes compensation vectors and rotates scan data based on sensed motion, enabling self-service registration that maintains accuracy while dramatically reducing time consumption.
Solution Approach 2:
The patent replaces manual mechanical registration operations with automated sensor-based pose estimation. Instead of manually aligning scans, the system uses IMU data and wheel encoder readings to computationally determine pose changes and automatically rotate scan data, substituting mechanical/manual processes with electronic sensing and computational geometry.
2Area of stationary object
If the scanner is moved during scanning to capture complete environment data, then coverage improves, but registration difficulty and error accumulation increase
Solution Approach 1:
The patent introduces sensor data (IMU and wheel encoders) as an intermediary to mediate between scanner motion and registration. These sensors provide real-time pose information that acts as a bridge, allowing the system to track scanner position and orientation during movement, thereby simplifying the registration of scans taken from multiple locations without manual intervention.
3Productivity
If automated transporter robot is used to move the scanning device, then scanning efficiency improves, but system complexity increases
Solution Approach 1:
The patent merges the scanning device with the automated transporter robot into an integrated mobile scanning system. The scanner, IMU, and wheel encoders are combined on a single mobile platform, allowing simultaneous acquisition of scan data and pose information. This merging improves scanning efficiency by enabling continuous movement and scanning while simplifying system architecture through integration rather than separate coordinated systems.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables efficient and accurate generation of 3D maps with reduced manual intervention, improving data quality and reducing the time and cost associated with scanning processes, while allowing for scanning in both autonomous and semi-autonomous modes.
Implementation Method 1
A scanning device is configured to capture scan-data of surrounding environment
Implementation Method 2
A TOF laser scanner is a scanner in which the distance to a target point is determined based on the speed of light in air between the scanner and a target point
Data Source
AI summary
A system includes a transporter robot with a motion controller that changes the transporter robot's poses during transportation. A scanning device is fixed to the transporter robot. One or more processors are coupled to the transporter robot and the scanning device to generate a map of the surrounding environment. At a timepoint T1, when the transporter robot is stationary at a first location, a first pose of the transporter robot is captured. During transporting the scanning device, at a timepoint T2, the scanning device captures additional scan-data of a portion of the surrounding environment. In response, the motion controller provides a second pose of the transporter robot at T2. A compensation vector and a rotation for the scan-data are determined based on a difference between the first pose and the second pose. A revised scan-data is computed, and the revised scan-data is registered to generate the map.