Lidar Fundamentals

LiDAR (Light Detection and Ranging) is a remote sensing technology that measures distances by emitting laser pulses and calculating the time it takes for these pulses to return after reflecting off objects. It generates precise, three-dimensional representations of environments and objects, useful in fields such as autonomous driving, robotics, geography, and visual effects.

How Lidar Works

Lidar systems emit short laser pulses toward objects or environments. These pulses reflect off surfaces and return to the scanner, where the system precisely measures the time it takes for each pulse to travel from the scanner to the object and back. By multiplying this travel time by the speed of light, the LiDAR system calculates the distance between the scanner and the object. Repeating this process millions of times creates a dense “point cloud,” a highly detailed 3D representation of the scanned environment.

Types of Lidar Scanners

Two primary types of Lidar scanners include Terrestrial and SLAM-based systems.

Terrestrial Lidar

• Description: Stationary scanning systems mounted on tripods, designed for high accuracy and detailed 3D capture.

• Example Hardware: Leica BLK360, Leica ScanStation P50, Faro Focus.

• Strengths:

  • Extremely high accuracy (sub-millimeter to centimeter scale).

  • Stable and reliable data for architectural, archaeological, and civil engineering projects.

  • Superior detail capture of structures and environments.

• Weaknesses:

  • Stationary operation limits mobility and flexibility.

  • Time-consuming scanning process.

  • Requires multiple setups for comprehensive environment coverage.

SLAM (Simultaneous Localization and Mapping)

• Description: Mobile scanning systems leveraging simultaneous localization and mapping algorithms, enabling scanners to be handheld or mounted on drones or vehicles.

• Example Hardware: NavVis VLX, Xgrids K1.

• Strengths:

  • High mobility and ease of use in dynamic environments.

  • Rapid data collection, ideal for large or complex spaces.

  • Real-time mapping capabilities, beneficial in robotics and autonomous navigation.

• Weaknesses:

  • Generally lower accuracy compared to terrestrial scanners.

  • Data quality affected by motion, requiring sophisticated software processing.

  • Can struggle in feature-poor or highly dynamic environments.

Key Differences

• Accuracy: Terrestrial LiDAR has higher accuracy; SLAM-based LiDAR trades some accuracy for mobility and speed.

• Mobility: SLAM excels in dynamic, rapidly changing environments; Terrestrial LiDAR is ideal for stationary, detailed surveying.

• Applications: Terrestrial scanners suit engineering and architectural projects; SLAM scanners suit robotics, autonomous vehicles, and rapid environmental mapping.

Software and Typical Processing Workflow

1. Data Acquisition: Scanning environments using selected LiDAR hardware.

2. Pre-processing: Initial data registration and alignment, filtering noise, and cleaning.

3. Point Cloud Processing: Using software such as Leica Cyclone, Faro Scene, NavVis Ivion, CloudCompare, or Autodesk ReCap to create accurate and usable point clouds.

4. 3D Modeling and Analysis: Converting point clouds into detailed 3D models, conducting analysis or simulation in software like Autodesk Revit, Bentley Systems, or Blender.

5. Output and Visualization: Generating visualizations, reports, or animations suitable for client delivery or further applications.

Use Cases and Combining Scanners

• Use Terrestrial Scanners: For high-precision engineering, architectural, historical preservation, and forensic projects where accuracy is critical.

• Use SLAM Scanners: Ideal for large-scale, dynamic environments, indoor navigation, robotics, and rapid surveys.

• Combining Both Types: Effective in complex scenarios such as construction projects where high accuracy (terrestrial) is required for structural elements, while rapid updates and mobility (SLAM) benefit regular project tracking and progress monitoring.

Understanding these differences, strengths, weaknesses, and workflows enables effective use and integration of LiDAR technology for diverse application needs.