LiDAR Drives Our Autonomous Future

Sensors Insights by Neil Huntingdon

Cars, robots and other machines are becoming more intelligent thanks to several technology advances that help these smart machines operate and navigate more autonomously. One of the key technologies in the autonomous revolution is LiDAR, which stands for Light Detection and Ranging.

LiDAR works by firing laser pulses at a surface. The sensor then measures the amount of time the light takes to travel back. Light moves at a constant known speed so the machine can accurately determine the distance between itself and its target. Repeating this process in rapid succession, the sensor can build a complex 3D map of its surroundings or chosen target.

The dense point clouds provided by LiDAR data can create accurate and reliable 3D images of streets, large areas, mountainous terrain and other difficult to reach locations. Initially used in outer space missions by NASA, today LiDAR is ideal for several applications for the automotive industry, security systems, mapping and surveying, and agriculture and mining.

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Cameras & Radar

Modern cars use a combination of cameras and radar sensors to enable braking assistance, steering and other navigation applications. However, both cameras and radar have inherent disadvantages that make fully autonomous navigation difficult.

Figure 1

Cameras don’t work well in poor lighting conditions, like driving in the dark, and have difficulty navigating wet roads, which cause a glare. Radar is good for determining the speed at which objects are moving, but it can’t distinguish where exactly objects are; for example, whether a stopped vehicle is in its lane or on the shoulder of the road.

 

LiDAR + Camera + Radar = Solution

LiDAR can provide valuable 3D perception data in a variety of weather conditions and can help balance out the advantages and disadvantages of each solution. LiDAR, used in combination with cameras and radar, will be pivotal in ushering in the era of self-driving cars.

Figure 2

We’ll see LiDAR initially integrated into mainstream cars to provide Level 3 active safety features, and then over the next few years, LiDAR will enable Level 4 automation and eventually Level 5 capabilities. LiDAR is already being used in several pilot tests for self-driving cars around the world, and not just for private vehicles. The startup May Mobility has been actively testing its self-driving shuttle fleets, which leverage Cepton’s LiDAR sensors to autonomous navigate, in cities around the U.S.

 

But Is It Secure?

Security is another area where LiDAR can help supplement traditional solutions to provide a new level of efficiency. Similarly, to automotive use cases, the optimal solution is a combination of sensor technologies including LiDAR. For electronic security and safety applications LiDAR can be combined with network cameras to improve object detection accuracy and automate PTZ tracking.

LiDAR can help identify when a perimeter has been breached as well as classifying objects, enabling companies to identify potential threats and quickly act when needed. Object classification significantly reduces the number of false positives generated by security systems, enabling companies to more efficiently use their resources.

Figure 3

LiDAR software can also be programmed to classify alarms based on different types of situations. For example, one protocol might be set up when a person is approaching a security gate, while another protocol will be set up when a vehicle is approaching. This makes LiDAR ideal for a wide variety of security solutions for airports, corporate campuses, industrial settings, government facilities and beyond.

 

Solo Flight

With the proliferation of drones, 3D sensing technologies will play a key role in the mapping and surveying industries. Many drones today use a geo-reference payload, which consists of an initial measurement unit (IMU) and GNSS/GPS to provide accurate geo positioning. However, high-performance IMUs can be very expensive, making them much less accessible.

LiDAR can be integrated into Unmanned Aerial Vehicles (UAVs) for a lightweight and cost-effective mapping solution that’s also highly accurate. Some use cases for UAVs integrated with LiDAR include terrain mapping, urban mapping, and mapping of utility assets such as pipelines, powerlines, and various infrastructures. These maps can help urban planners decide what infrastructures to build and where, from skyscrapers to roadways. Even archeologists and scientists are using LiDAR to cover larger, more difficult terrains, enabling them to map out entire cities in just minutes.

 

Further Down The Food Chain

The agriculture and mining industries are also being revolutionized by LiDAR technology. Integrated LiDAR can map areas quickly and accurately, which is especially important for large areas like crop fields and tight spaces in mines. In agriculture, LiDAR can be used for automated tractor steering solutions to provide real-time 3D perception for autonomy and real-time decision-making capabilities.

Figure 4

LiDAR can also be used to survey fields from overhead with drones, providing valuable information about crop yields to further farmers’ precision agriculture initiatives. In mines, LiDAR can be used to generate clearer images of dark mining terrain and generate detailed surveys to detect if caves are unstable or the infrastructure is compromised. Equipping mining machines with LiDAR helps reduce the risk of miners getting injured or lost and greatly improves overall safety and efficiency.

Some of the key features to look for in a LiDAR solution are range, resolution, power efficiency, size and, of course, price. For applications that require visibility at a distance, LiDAR sensors will ideally have between a 150 to 200-meter range. Resolution determines how much a LiDAR sensor can see, so high-resolution sensors are important to provide an accurate 3D map.

 

Power, Size, & Cost

Another key consideration for LiDAR is power efficiency. This is especially true for machines that are in motion, such as vehicles and UAVs, to ensure that they can run longer. While early iterations of LiDAR solutions were quite bulky and heavy, today there are much more compact LiDAR sensors on the market.

The size of LiDAR sensors is extremely important in UAVs where lightweight solutions prolong flight time. Cars are another use case where small LiDAR sensors are valuable. LiDAR integrated into the body of the vehicle will provide cars with advanced perception while also maintaining a vehicle’s aesthetics, which will be very important once cars with LiDAR hit the mass market.

Cost is another a key consideration for LiDAR. While big organizations and governments have been able to take advantage of traditional, expensive LiDAR solutions, we’re now seeing a new wave of more affordable solutions. Reliability and scalability are two other critical considerations. LiDAR solutions need to be able to withstand harsh conditions and work over a long period of time to keep people safe and need to be ready for mass production at scale for applications like autonomous cars.

As LiDAR continues to evolve and deliver higher resolution images with longer range, lower cost, in smaller form factors, LiDAR will continue to transform more industries and improve daily life.

 

About the author

Neil Huntingdon is the Vice President of Business Development at Cepton Technologies, Inc. Continuing his work supporting the Security, Safety and Smart City markets with innovative sensor technology solutions, Neil Huntingdon is spearheading Cepton’s introduction of its Micro Motion Technology LiDAR sensor-based people detection and tracking solution. Neil has previously worked with major security systems integrators, global distribution partners and developed and managed partnerships with leading VMS and PSIM vendors as well as engaging the IP camera vendor eco-systems and partners.

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