Overview
Growing interest in autonomous driving has driven major advances in LiDAR technology. These 3D LiDAR sensors are valued for accurate environmental perception by measuring distance with laser pulses, making them important safety components for autonomous transport. The mobility sector has strong demand for these sensors and continues to pursue further development of the technology.
Before the recent surge in interest, LiDAR had been used for years in research, mapping, and spatial analysis. Early systems were expensive, often large, and required regular maintenance. Advances in technology have made sensors more capable, lower maintenance, less costly, and easier to use, even for users without specialized 3D data analysis expertise.
New Applications
This transition has attracted broader industry adoption and enabled new application areas, including:
- Bulk volume monitoring: LiDAR-based solutions generate inventory data for bulk materials that were previously difficult to collect with alternative methods. These solutions can integrate real-time data automatically into inventory management systems, improving process efficiency in agriculture, construction, and recycling.
- Security systems: LiDAR sensors perform well for intrusion detection, offering high reliability and significantly reduced false alarm rates, making them suitable for protecting critical infrastructure such as power plants and airports.
- Crowd management: LiDAR enables anonymous tracking of crowd movement patterns. For example, tourist destinations can use LiDAR to monitor visitor counts and offer real-time alternative suggestions via mobile apps when an area approaches capacity, helping to reduce congestion.
What is LiDAR?
LiDAR stands for light detection and ranging, and its operating principle is distance measurement using laser beams. Early 3D LiDAR sensors, such as those seen on early autonomous test vehicles, were rotating LiDARs. These devices featured large components mounted on the roof that mechanically rotated to gather environmental data. Early iterations were costly and required regular maintenance due to moving parts.
To address these drawbacks, companies such as Blickfeld adopted solid-state LiDAR technology, removing the need for mechanical parts. This advancement resulted in more reliable, smaller, and more cost-effective sensors.
In solid-state scanning LiDAR, laser diodes emit hundreds of thousands of laser pulses per second to MEMS mirrors (microelectromechanical systems) that oscillate at their respective frequencies. These MEMS mirrors are precisely positioned to deflect the laser beam in a conical pattern without mechanical wear. Mature micro-sensor manufacturing enables reliable, low-cost mass production of these components.
Emitted light pulses reflect off objects in their path and are captured again by the sensor. By measuring the time it takes light to travel, LiDAR computes precise distances between the sensor and detected objects using the time-of-flight principle. This process creates highly accurate 3D representations of the surrounding environment, known as point clouds.
Essentially, the technology works similarly to radar, which uses electromagnetic waves to measure distance and velocity. Radar is particularly reliable when encountering metal surfaces but less so for other materials. Generally, radar provides less detail than LiDAR. 3D LiDAR can capture an object’s spatial position and shape with high precision and is largely independent of surface material.
From 1D to 3D Imaging
The capabilities of different LiDAR sensors depend on their field of view, which determines how much information they can collect:
1D LiDAR: Uses a single laser pulse directed in one direction, allowing distance measurement at a specific point. This is suitable for applications such as toll booths but cannot determine object type, size, or shape.
2D LiDAR: Uses horizontally rotating laser pulses to measure distance and motion direction, providing additional information about object shape by analyzing reflection points and distances. 2D LiDAR sensors are widely used in industrial automation and robotics. However, objects are only detected at the sensor’s plane height, preventing accurate size assessment. For example, a knee-high object in an alarm system may trigger frequent false alarms because small animals can cross the detection plane. Raising the observation plane may allow people to avoid detection by crawling or crouching.
3D LiDAR: By rotating laser pulses both horizontally and vertically, 3D LiDAR creates a conical field of view that captures three-dimensional spatial data. This third dimension is essential for forming an accurate spatial representation of the environment, providing valuable data across many applications, and enabling new possibilities. In security systems, 3D LiDAR ensures detection of every intrusion into a protected area and determines the size of the intruding object. Software can set size thresholds to trigger alarms, significantly reducing false alarms and unauthorized entries.
In security applications, LiDAR users can define zones where any intrusion is reliably detected with very low false alarm rates. (Image: Blickfeld)
Image Recognition and LiDAR
3D LiDAR sensors provide direct distance information, while cameras mainly capture light and color and do not measure spatial information directly. These direct distance measurements offer a significant advantage. Although modern AI-enabled software can infer 3D information from camera data, 3D LiDAR delivers spatial information directly, faster, and more accurately. This is especially beneficial for autonomous vehicles and unmanned aerial vehicles that rely on accurate distance measurements for safe navigation and collision avoidance.
Next Level: Smart LiDAR
Smart LiDAR sensors require advanced optical and electronic hardware components and powerful software to analyze collected data. In many cases, 3D data from the sensor is transmitted to an external computer where perception software performs analysis.
Blickfeld simplified this process with the Qb2, a LiDAR sensor that integrates the necessary data analysis software. The sensor’s "eye" and "brain" are combined in a single device, allowing immediate access to available data without extra computer hardware or network attachments. This makes 3D data accessible to a broader audience, including those without specialized 3D data analysis skills.
The resulting information can be transmitted directly and seamlessly into IoT ecosystems or the cloud using standard communication protocols such as MQTT and PI. This allows remote staff to access results in real time and view them in a standard web browser on tablets or smartphones. Because only small amounts of data need to be transmitted, Wi-Fi transmission is feasible, further reducing cable requirements. This is particularly advantageous in systems with multiple sensors, such as those used to monitor large bulk material inventories, and simplifies installation and operation.
LiDAR and Industry Digitization
Enterprises that adopt 3D LiDAR technology can realize immediate benefits from precise real-time information, enabling digitalization and more efficient processes. 3D LiDAR has the potential to significantly advance supply chain digitization across industries and play a key role in solving tasks that were previously costly, labor-intensive, or impractical. Integrating software into the device allows many users to benefit from 3D data even without specialized expertise.
