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Challenges ahead of LiDAR technology

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What is LiDAR?

Light detection and ranging, commonly known as LiDAR, is a technology used to detect and range objects in space. LiDAR systems use reflected light to create a three-dimensional model of their surroundings laser Measure the distance of an object. 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 that require accurate object detection or ranging. It can have a resolution of a few centimeters at a distance of 100m, much better than a few meters of radar. It has become the preferred choice for various ranging applications.

Currently, the main application of LiDAR is in vehicles for ADAS and autonomous driving functions. The race to create a low-cost he LiDAR system that offers safe self-driving capabilities is happening as you read this. However, the technology has some issues to address and must beat competing technologies before it can become a winner. Let’s take a look at the main challenges ahead of LiDAR.

1. The Range

LiDAR manufacturers claim the technology has a range of 100m, possibly 200m. These claims are misleading because scope can be defined in many different ways. Even if a LiDAR system can detect its presence, it may not be as accurate in detecting objects at greater distances in real-world situations.

For example, imagine a self-driving car with LiDAR driving down the road. A dark object 100m away may not be detected in its entirety due to reflections, and LiDAR may not be able to create an accurate 3D map from the point cloud of the reflected laser beam. The same is true if the bright object is too close to the vehicle and the dark object is far away. Cases like this call into question the claimed scope of his LiDAR device.

Range issues should be confirmed through testing in real conditions. The range issue is not about specific situations, but about LiDAR limitations in different cases. Manufacturers and researchers must come up with a general solution to this problem to ensure system accuracy.

2. Safety concerns in edge cases

As mentioned earlier, the issue of LiDAR accuracy under certain conditions can be a big deal when it comes to safety.In conditions such as fog, rain and snow bright sun behind white object, the problem of face detection in all kinds of self-driving cars. This is dangerous, and in worst-case scenarios can even be fatal.

Weather conditions can block LiDAR laser beams and cause similar problems. Fog and rain are known to limit the use of LiDAR as they limit the transmission and reflection of laser beams in such conditions. Whether it’s the weather or objects being carried by the wind, the surroundings mapped by LiDAR can be erroneous and the information misleading.

The inability to distinguish weather phenomena or everyday objects from vehicles on the road can be a major problem for the self-driving car industry. However, this problem is already being tackled with higher power lasers and better algorithms that can use the data available in such conditions to get the best results.

3. Cost

Another big problem with LiDAR is its high cost. Although costs have fallen rapidly over the years, LiDAR systems are still significantly more expensive than alternative camera vision systems. LiDAR still costs about $500 apiece, but Tesla’s eight cameras cost less than $100. In a competitive market with low margins, it can make a big difference.

The cost of LiDAR will continue to fall based on what we have seen over the years. In 2015, the price of a LiDAR unit was $75,000. At some point, the cost reduction will slow down, but the accuracy of LiDAR may soon put it in a competitive range with cameras.

4. Reliability

A typical LiDAR device is an electromechanical system with multiple moving parts. Such systems tend to be unreliable and can experience more failures and breakdowns. Add to that the working conditions in which the vehicle goes through dirt, water, vibration, and all sorts of real-world conditions, and it may not last long before critical systems fail.

Reducing moving parts enables the creation of highly reliable LiDAR. This is an engineering problem and can be solved with better design. Several solid-state LiDAR systems have been created and may be the ultimate solution to this problem in the long term.

LiDAR is a promising technology for self-driving cars. With resources invested in research and development by automotive and laser manufacturers, there is great potential for finding solutions to all challenges. LiDAR accuracy could make self-driving cars safer and the future closer to all fans of autonomous technology. If you’re one of hers out there, keep an eye out for LIDAR space.

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