Challenges Facing LiDAR Technology


What is LiDAR?

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

LiDAR is used in various applications where precise detection or ranging of objects is required. It can have a resolution of a few centimeters at a distance of 100m which is much better than the few meters of radar. The accuracy of LiDAR makes it the preferred choice for altimetry, contour mapping, scanning for AR experiments like in the new iPhone, and various other ranging applications.

Today, the main application of LiDAR is in vehicles for ADAS and autonomous driving functions. The race to create a low-cost LiDAR system that provides safe autonomous driving capabilities is unfolding as you read this. However, the tech has a few issues to contend with and a competing tech to beat before emerging victorious. Let’s look at the main challenges in front of LiDAR.

1. The range

LiDAR makers claim the technology has a range of 100m and even 200m in some cases. These statements can be misleading because the range can be defined in different ways. A LiDAR system may not be as accurate at detecting objects at a greater distance in real-world situations, even though it can detect a presence.

For example, let’s say a self-driving car with LiDAR is moving down a road. A dark object at 100m may not be detected in its entirety due to reflectivity and LiDAR may be unable to create an accurate 3D map from point clouds of reflected laser beams. The same applies to the case where a bright object is too close to the vehicle and a dark object is further away. Such cases call into question the claimed ranges of LiDAR devices.

The question of the range must be verified by tests in real conditions. The issue of range is less about specific situations and more about the limitations of LiDAR in various cases. Manufacturers and researchers must find a general solution to this problem to ensure the accuracy of the system.

2. Security issues in extreme cases

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

Weather conditions can obstruct LiDAR laser beams and cause similar issues. Fog and rain are known to limit the use of LiDAR due to the limited penetration and reflection of laser beams in such conditions. Whether it is the weather or an object carried by the wind, the environment mapped by LiDAR becomes erroneous and the information can be misleading.

The inability to tell the difference between a weather phenomenon or everyday objects and a vehicle on the road can be a game changer for the autonomous automotive industry. However, this problem is already being worked out using high power lasers and better algorithms that can use the data available under such conditions to get the best results.

3. Cost

Another major issue with LiDAR is its 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 around $500 per while eight cameras on a Tesla cost less than $100. In a competitive market with low margins, this can make a huge difference.

The cost of a LiDAR will continue to drop based on what we have seen over the years. In 2015, a LiDAR unit cost $75,000. As cost reduction slows down after a certain point, with its higher accuracy, LiDAR may soon enter a competitive range against cameras.

4. Reliability

Common LiDAR devices are electromechanical systems with multiple moving parts. Such systems tend to be less reliable and may experience more breakdowns and breakdowns. Add to that the working conditions of the vehicles where they go through dirt, water, vibration, and all sorts of real-world conditions and you have an important system that might not last long before failing.

Creating reliable LiDAR is possible by reducing moving parts. This being an engineering problem, it can be solved with better designs. Some solid-state LiDAR systems have been created, which may also become the final solution to this long-term problem.

LiDAR is a promising technology for autonomous vehicles. With the resources invested in research and development by automotive and laser manufacturers, it has great potential to find solutions to any challenge. The precision of LiDAR can make self-driving cars safer and bring the future closer to all fans of self-driving 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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