Autonomous Systems in the Real World
There are many examples of autonomous systems already in operation in the real world. Examples include simple robots on the factory floor performing the same task day after day as well as self-driving cars.
With simple robots, the situation is straightforward. The machines are taught what their job is, and the variables remain constant, allowing them to complete their function without additional intervention being required. In the latter case, the situation is quite a bit more complicated. Vehicles are not static, and the world around them constantly changes.
Here, vehicles are surrounded by a system of sensors, including cameras, radar, and lidar, to build a 3D image of the vehicle and everything around it. Using GPS tools, vehicles are able to plot a route to their destination and, through real-time computation, understand the obstacles in their way.
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Autonomous Systems in the World of AI
Current technologies in use for automated vehicles are in the very early stages of launch. Innovations using AI can:
- enhance these systems further helping them differentiate road signs in variable weather conditions,
- understand the actions of parked and moving vehicles to ensure appropriate action is taken,
- deal with accidents and other road hazards in a safe manner.
In fact, expanding on the individual vehicular autonomous system, future transport systems could be fully automated, helping coordinate and dispatch vehicles across a whole city. Autonomous systems can, in fact, be used across a gamut of industries and verticals, and their only limitation is our own imagination.
The use of AI and autonomous systems go far beyond what has already been explored. While vehicular autonomous systems can be significantly enhanced to provide even greater safety and security, this is not the only benefit of AI and autonomous systems.
