A comparison of vision sensing technologies in autonomous systems

 Autonomous systems rely on sensors to gather information about their environment and make decisions. Sensors can be divided into two main categories: passive and active. Passive sensors, such as inertial measurement units (IMUs) and image sensors, detect incident light or changes in parameters without emitting a source signal. Active sensors, such as radar and lidar, emit their own source signal and measure how it changes by detecting reflections.


The three main sensor modalities used in autonomous systems today are radar, lidar, and image sensors. These technologies are all used for object detection and collision avoidance, as opposed to location or navigation. They provide visibility of objects that are relevant to the autonomous system, and anything that is not relevant can be safely disregarded.


When comparing these technologies, one way to differentiate them is by their use of the electromagnetic (EM) spectrum. Radar systems operate from around 5 MHz to 300 GHz, with higher frequencies delivering higher resolution. Lidar systems use energy in the part of the spectrum occupied by light, at frequencies in the 100s of THz. Image sensors predominantly operate in the visible part of the EM spectrum, although many can now detect in near-infrared to improve low-light performance.


Each of these technologies has its own strengths and weaknesses. Radar systems are good at detecting objects in bad weather and at long ranges, but their resolution is lower than lidar or image sensors. Lidar systems provide high-resolution data, but they are affected by interference from light sources and can be affected by dust or other particles in the air. Image sensors are the most similar to human vision, providing data that is familiar and often in color, but they can be affected by low-light conditions or changes in lighting.


In autonomous systems, a combination of sensor modalities is often used to provide a more complete picture of the environment. For example, radar may be used to detect objects at long ranges, while lidar and image sensors provide higher-resolution data for closer objects. By using a variety of sensing modalities, autonomous systems can gather the right kind of data in the right way and make decisions with greater accuracy and safety.

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