For vehicles to truly be autonomous, it requires multiple sensors of different types to provide simultaneous streams of data about the environment around them. Vision systems themselves do not provide enough context for a vehicle to safely operate autonomously.
Light detection and ranging (LiDAR) systems have become an essential component of any autonomous vehicle, whether it’s drones or cars or trucks. LiDAR provides information about a vehicle’s surroundings that radar and vision systems simply cannot offer, even in harsh weather conditions.
So how are these two systems used together to create autonomous navigation?
How Vision Systems are Used in Autonomous Vehicles
First, it’s important to understand how vision systems are used in autonomous vehicles. They are primarily used for the detection and classification of objects – a key task in any autonomous vehicle. Vision systems, often leveraging advanced machine vision algorithms, can first detect that an object exists, and then leveraging their extensive training, identify what that object is and translates this into an action.
Vision-based detection and classification may include lane finding, road curvature estimation, obstacle detection and classification, and traffic sign or traffic light detection and classification, among many other basic tasks. All of this must occur at very high speeds so that the autonomous vehicle can make decisions in a timely manner.
Vision Systems and LiDAR Together for Autonomous Navigation
LiDAR operates in poor weather conditions and can detect the distance and rate of other objects far better than vision systems can. This provides critical information in addition to that gathered through vision systems. When working together, however, these two systems can fully detect their surroundings in any weather, gathering contextual information about all of their surroundings.
Some new forms of navigation involve combining vision system pixels with LiDAR voxels for simultaneous and faster processing of both data streams, giving vehicles more time to make critical safety and navigational decisions. Other new algorithms can take these two streams of data and combine them for highly accurate 3D models of the vehicle’s surroundings, allowing for autonomous navigation with greater awareness of the surrounding environment at close range.
Vision systems and LiDAR are a powerful combination. They work together in many different ways. The goal is to provide as much information as possible, as accurately as possible, to enable autonomous navigation.
To learn more on this topic, read our archived feature article on data fusion for autonomous navigation to take a deeper dive into the subject.