Challenges to LiDAR technology

Challenges to LiDAR technology

What is LiDAR?

Light detection and ranging, more commonly known as LiDAR, is a technology used to detect objects in space and remotely. A LiDAR system creates a three-dimensional model of any environment using reflected light lasers to measure the distance of objects. In this way, it is very similar to radar technology, the only difference being that it uses lasers instead of radio waves.

LiDAR is used in a variety of applications where accurate object detection or ranging is required. It can have a resolution of a few centimeters at a distance of 100 m, which is significantly better than the multi-meter radar. LiDAR’s accuracy makes it the preferred choice for height measurement, contour mapping, scanning for AR experiences like the new iPhone, and a variety of other applications.

Today, the main application of LiDAR is in ADAS and autonomous driving functions. As you read this text, the race is on to develop a low-cost LiDAR system to enable safe autonomous driving capabilities. However, the technology has some problems to solve, and the competing technology needs to be overcome before it can be declared the winner. Let’s take a look at the main challenges of LiDAR.

1. Range

LiDAR manufacturers claim that the technology works for 100m, and in some cases even 200m. These statements can be misleading because the range can be defined in different ways. A LiDAR system may not be accurate enough to detect objects at greater distances in real situations, even if it can detect presence.

Let’s say an autonomous car with LiDAR is moving down the road. A dark object at 100m may not be detected entirely due to reflection, and LiDAR may not be able to create an accurate 3D map from point clouds of reflected laser beams. The same is true when a bright object is too close to the vehicle and a dark object is further away. In such cases, the specified ranges of LiDAR devices are in doubt.

The range issue must be verified by testing under real-world conditions. The range question is less about specific situations and more about the limitations of LiDAR in various situations. Manufacturers and researchers must come up with a common solution to this problem to ensure system accuracy.

2. Security issues in border cases

As mentioned above, the issue of LiDAR accuracy under certain conditions can be critical if it affects safety. In conditions such as fog, rain, snow, etc bright sun behind white object, autonomous vehicles of all kinds face detection problems. This can be dangerous and even fatal in the worst case scenario.

Weather conditions can interfere with LiDAR laser beams causing similar problems. Fog and rain are known to limit the use of LiDAR due to the limited penetration and reflection of laser beams in these conditions. Whether it’s the air or some object carried by the wind, the environment projected by LiDAR becomes inaccurate and the information can be misleading.

The inability to distinguish weather phenomena or everyday objects from a vehicle on the road could be the bane of the self-driving car industry. However, this problem is already being solved with high-powered lasers and better algorithms that can use the available data under these conditions to achieve the best results.

3. Price

Another major issue with LiDAR is the higher cost. Although costs have come down rapidly over the years, a LiDAR system is still significantly more expensive than the alternative camera vision system. LiDAR still costs about $500, while Tesla’s eight cameras cost less than $100. In a competitive market with tight margins, this can make a big difference.

The cost of LiDAR will continue to decrease based on what we have seen over the years. Back in 2015 The LiDAR unit cost $75,000. Although costs decrease more slowly after a certain point, LiDAR’s increased accuracy may soon bring it into competitive range with cameras.

4. Reliability

Typical LiDAR devices are electromechanical systems with several moving parts. Such systems are generally less reliable and may experience more breakdowns and failures. Add to that the operating conditions of the vehicles, where they are exposed to dirt, water, vibration and all kinds of real-world conditions, and you have a critical system that can last a long time before it fails.

Creating a reliable LiDAR can be achieved by reducing the moving parts. This is an engineering problem and can be solved with a better design. Some solid-state LiDAR systems have been developed and may eventually become the ultimate solution to this problem as well.

LiDAR is a promising technology for autonomous vehicles. With automotive and laser manufacturers investing resources in research and development, it has great potential to find solutions to all challenges. The accuracy of LiDAR can make self-driving cars safer and bring the future closer for all fans of autonomous technology. If you’re one of those, keep an eye on the LIDAR space because it’s only going to get better.

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