Challenges ahead of LiDAR technology

Challenges ahead of LiDAR technology

What is LiDAR?

Light Detection and Ranging, better known as LiDAR, is a technology used to detect and remove objects in a room. A LiDAR system uses reflections to create a three-dimensional model of any environment laser 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 various applications where accurate object detection or removal is required. It can have a resolution of a few centimeters at a distance of 100 m, which is significantly better than the several meters of radars. LiDAR’s accuracy makes it the preferred choice for height measurement, contour mapping, scanning for AR experiences 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. As you read this, the race is on to develop a cost-effective LiDAR system that offers safe autonomous driving capabilities. However, the technology has some issues to overcome and beat a competing technology before emerging victorious. Let’s look at the biggest challenges ahead of LiDAR.

1. The range

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

For example, suppose an autonomous car with a LiDAR is moving down a street. A dark object 100m away may not be fully detected due to reflectivity and the LiDAR may not be able to create an accurate 3D map from the point clouds of the reflected laser beams. The same applies when a bright object is too close to the vehicle and a dark object is further away. Such cases challenge the claimed ranges of LiDAR devices.

The question of range must be checked by tests under real conditions. The question of range is less about specific situations and more about the limitations of LiDAR in different cases. The manufacturers and researchers need to find a general solution to this problem to ensure the accuracy of the system.

2. Safety concerns in borderline cases

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

Weather conditions can obstruct LiDAR’s laser beams and cause similar problems. 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’s weather or an object being carried around by the wind, the environment LiDAR maps becomes inaccurate and the information can be misleading.

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

3. The cost

Another big problem with LiDAR is the higher cost. While 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 apiece, while eight cameras on a Tesla cost less than $100. In a competitive, low-margin market, this can make a world of difference.

The cost of a LiDAR will continue to come down based on what we’ve seen over the years. As recently as 2015, a LiDAR unit cost $75,000. While cost reduction slows down at a certain point, LiDAR with its higher accuracy could soon enter competitive territory against cameras.

4. Reliability

Common LiDAR devices are electromechanical systems with multiple moving parts. Such systems tend to be less reliable and can experience failures and failures more frequently. Add to that the working conditions of vehicles, which expose them to dirt, water, vibration and all sorts of real-world conditions, and you have a vital system that may not last long before it fails.

Creating a reliable LiDAR is possible by reducing moving parts. Since this is a technical problem, it can be solved with better designs. A few solid-state LiDAR systems have been developed that could also be the definitive solution to this problem in the long run.

LiDAR is a promising technology for autonomous vehicles. With the resources that car and laser manufacturers invest 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 to all fans of autonomous technology. If you’re one of them, keep an eye on the LIDAR room as it’s only going to get better.

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