Using ROCK Desktop's GCP Alignment Tool (SLAM)

This guide provides a clear, step-by-step tutorial on using the ROCK Desktop's GCP (Ground Control Point) Alignment tool. The process is broken down into simple steps for ease of understanding.

Requirements:

• ROCK R3 Pro for SLAM data collection.
• A computer with ROCK Desktop installed.
• Ground Control Points (GCPs).
• A CSV file containing your GCPs.

Understanding the Importance of GCP Alignment in ROCK Desktop

Before diving into the instructions, it's crucial to comprehend the significance of the GCP alignment feature in ROCK Desktop.

What is GCP Alignment?

GCP Alignment: This is a process in ROCK Desktop that uses Ground Control Points to enhance the accuracy of your SLAM data sets.
Improving Data Accuracy: With GCP alignment, you can achieve a higher level of precision in your LiDAR data, often reaching sub-centimeter accuracy.

How Does It Enhance Data Sets?

Refines Positional Accuracy: By aligning your data with fixed, known points on the ground (GCPs), the tool corrects and refines the positional accuracy of your entire data set.
Versatile and Precise: This tool is versatile enough to handle data collected in various environments, whether indoors or outdoors.

Sources of GCPs:

Multiple Sources: GCPs can be obtained from different sources, providing flexibility in how you gather this crucial data.
GNSS Equipment: Such as a base rover pair or an RTK GNSS receiver.
Total Station: For precise, ground-based measurements.
Aerial LiDAR: Using the ROCK R3 Pro in a drone configuration to capture aerial LiDAR data.

Step-by-Step Instructions

Step 1: Collect SLAM Data

• Use the ROCK R3 Pro to collect SLAM data from your desired location.
  

Step 2: Launch ROCK Desktop

• On your computer, open the ROCK Desktop software.

Step 3: Process Your Data

• Copy SLAM Data to Your Computer: Before you start processing, ensure that all the SLAM data collected with the ROCK R3 Pro is copied to your local machine. This is an important step to ensure that the data is readily accessible for processing.
• Launch ROCK Desktop: Open ROCK Desktop on your computer.
• Select “Process ROCK Data”: In the software, choose the option to process your ROCK data.
• Choose Your Data Folder: Navigate to and select the acquisition folder where your copied SLAM data is stored. This folder should contain all the data from your recent collection session.

By following these steps, you ensure that all necessary data is properly positioned on your local machine for efficient processing in ROCK Desktop.

Step 4: Configure Data Processing

• Specify your data collection environment (outdoor or indoor).
• Select the capture mode (e.g., handheld).

Step 5: View Your Data

• Processing Time: Once you select your SLAM data folder, ROCK Desktop will process the data to create the visualized LiDAR dataset. This processing might take a few minutes.
• 3D Point Cloud Display: After processing, the software will display a 3D Point Cloud, showing your collected SLAM data in a visual format.

Step 6: Add GCPs

• Open Alignment Feature: Click on the “Align SLAM” icon in ROCK Desktop to start the GCP alignment process.
• Select Projection First: Before uploading your GCPs, first select the correct projection for your control points. This is crucial for ensuring that the GCPs align correctly with your data.
• Upload GCPs: After setting the correct projection, upload your CSV file containing the GCPs.
• Verify Control Points: Once uploaded, take a moment to check the accuracy and completeness of the control points.

Step 7: Align Data with GCPs

• Begin with Coarse Alignment: Start by roughly aligning the SLAM data with the real world using the GCPs. This coarse alignment involves selecting a minimum of four GCPs, ideally placed at different corners of the dataset.
• Purpose of Coarse Alignment: This initial step is critical for orienting the overall dataset in relation to real-world coordinates, providing a framework for the subsequent fine-tuning.
• Match GCPs with 3D Point Cloud: Carefully match each of the selected GCPs with their corresponding points on the 3D Point Cloud.

Step 8: Fine-Tune Alignment

• Refine GCP Alignment: After establishing the coarse alignment, proceed to the fine-tuning phase. This involves precisely adjusting each GCP to its exact location on the 3D Point Cloud.
• Importance of Fine-Tuning: This step is essential for achieving maximum accuracy, ensuring that each control point accurately reflects its real-world position.
• Manual Adjustments: Use ROCK Desktop's tools to manually adjust each GCP. Sometimes, a LiDAR point might not exactly coincide with a GCP location, requiring manual alignment.
• Optimal Number of GCPs: The number of GCPs needed for fine-tuning varies based on the dataset's complexity. More GCPs generally result in better accuracy, particularly for detailed or large-scale areas.

Step 9: Start the Alignment

• Click “Start Alignment” to initiate the process of refining your data set.

Step 10: Edit & Trim Data

Editing and trimming your 3D Point Cloud in ROCK Desktop is a crucial step in refining your final LiDAR dataset. This step determines what part of your collected data is most relevant and accurate for your needs.

Understanding the Importance of This Step:

• Refining Data Quality: This process helps in removing unnecessary or less accurate data, enhancing the overall quality of your point cloud.
• Focus on Relevant Areas: By trimming, you focus on the areas of interest, which is essential for projects that require high precision in specific locations.

Using Angle Gate and Range Gate:

• Angle Gate: The angle gate feature allows you to include data points within a specific angular field of view. This is particularly useful when you want to exclude points that are outside a certain angular range from your sensor.
  • Rationale: Use the angle gate when you need to focus on data from specific directions or angles, which can be critical in environments with obstructions or specific geometric requirements.
• Range Gate: The range gate lets you include data points within a certain distance range from your sensor.
  • Rationale: Apply the range gate when you want to focus on data that falls within a specific proximity. This is especially useful to eliminate distant points that might be less accurate or irrelevant.
    
    

Selecting the Trajectory:

• Trajectory Selection: This involves choosing the path that your ROCK R3 Pro took while collecting the data.
• Significance: Selecting the trajectory is vital as it determines which part of the captured data is included in the final point cloud. It's essential for projects where the path of movement directly impacts the data's relevance and accuracy.
  
  

Finalizing Your Point Cloud:

• After applying the angle and range gates, and selecting the appropriate trajectory, review your edited point cloud.
• Ensure that the retained data aligns with your project's objectives and requirements.
• The final point cloud, post-editing and trimming, will be the dataset used for further analysis or integration with other data sets.

By comprehensively understanding and applying these editing and trimming features in ROCK Desktop, users can significantly enhance the relevance, precision, and quality of their final LiDAR datasets.

Step 11: Upload & Share

• Once processing is complete, upload your data to ROCK Cloud for access and sharing.

Conclusion

Following these steps will enable you to accurately align your SLAM data with GCPs using the ROCK Desktop software. This guide aims to provide a straightforward and efficient approach to utilizing this powerful tool.