Challenges to LiDAR technology

What is LiDAR?

Light Detection and Ranging, better known as LiDAR, is a technology used to detect and range objects in space. The LiDAR system creates a three-dimensional model of any environment using reflectance 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 a variety of applications where accurate detection or ranging of objects is required. It can have a resolution of a few centimeters at a distance of 100 meters, which is significantly better than several meters of radar. LiDAR’s accuracy makes it a preferred choice for altimetry, contour mapping, scanning for AR experiences like the new iPhone, and various other ranging applications.

Today, the main application of LiDAR is in vehicles for ADAS and autonomous driving functions. The competition to create a low-cost LiDAR system that provides safe autonomous driving capabilities is underway as you read this. However, the technology has some issues to work through and competing technology to beat before it emerges victorious. Let’s look at the main challenges facing LiDAR.

1. The range

LiDAR manufacturers 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 in detecting objects at a greater distance in real-life situations, even if it can detect presence.

For example, let’s say an autonomous LiDAR car is driving down a road. A dark object 100 meters away may not be fully detected due to reflectivity, and LiDAR may not be able to create an accurate 3D map of point clouds of reflected laser beams. The same applies to the case when a bright object is too close to the car and a dark object is further away. Such cases call into question the claimed ranges of LiDAR devices.

The range issue should be verified through real-world testing. The range question is less about specific situations and more about the limitations of LiDAR in different cases. Manufacturers and researchers need to come up with a common solution to this problem to ensure the accuracy of the system.

2. Safety Considerations in Edge Cases

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

Weather conditions can interfere with LiDAR laser beams to cause similar problems. Fog and rain are known to limit the use of LiDAR due to the limited penetration and reflection of laser beams under such conditions. Whether it’s the weather or some object being blown around by the wind, the surroundings mapped by LiDAR become inaccurate and the information can be misleading.

The inability to differentiate between weather phenomena or everyday objects and a vehicle on the road could be a problem for the autonomous car industry. However, this problem is already being worked on with the help of high-power lasers and better algorithms that can use the available data in such conditions to get the best results.

3. The price

Another major problem with LiDAR is its higher cost. Although costs have fallen rapidly over the years, the LiDAR system is still significantly more expensive than the alternative camera vision system. LiDAR still costs about $500, while eight Tesla cameras cost less than $100. In a competitive market with low margins, this can make a huge difference.

The cost of LiDAR will continue to decrease based on what we have seen over the years. As recently as 2015, a single LiDAR unit cost $75,000. Although cost reduction slows over time, with its higher accuracy, LiDAR may soon enter a competitive range against cameras.

4. Reliability

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

Creating a reliable LiDAR is possible by reducing the moving parts. Since this is an engineering problem, it can be solved with better designs. Some solid-state LiDAR systems have been developed, which may also become the ultimate solution to this problem in the long run.

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

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