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Autonomous transport paves the way for self-driving cars

Posted: 12 Apr 2016     Print Version  Bookmark and Share

Keywords:Seegrid  autonomous transport  autonomous car  IR  UV 

The level of apprehension presented by the public towards autonomous cars still remains to be a thick and solid wall that carmakers are still having a hard time finding a way around of. It continues to breed considerable controversy because of its potential to replace humans behind the wheel.

However, that promise remains as it is. The technology is not robust enough yet to start building a significant presence on the world's highways and byways. But there's a subset of autonomous cars that is robust enough to start making its mark: autonomous transport. This technology can provide insights into potential evolutionary steps for autonomous cars.

Autonomous transport systems work not in the wide-open spaces of the world, but in confined and relatively controlled spaces such as factories or warehouses. The robotic stock delivery systems that Amazon uses are one example. These gadgets carry towers full of supplies around to workstations so that human packers can retrieve items and put them in boxes to fill orders.

But these robots require a specially-prepared environment. Look closely at the video and you will see stripes on the floor that are almost, but not quite, invisible. Those are tracks the robots must follow as they move about, and probably are quite distinctive under IR or UV light, allowing the robot to see them while remaining subtle to human eyes. Such guided movement is a first evolutionary step in autonomous transport.

A second evolutionary step has been taken by Seegrid, which provides transport vehicles with 360° vision. The devices use their vision capability to first map their surroundings and then to navigate based on that internal map. This frees the robots from the need for laying stripes or otherwise modifying the environment. They are able to operate with greater freedom.

These devices are not totally autonomous, however, in that they cannot choose their own path to follow. Instead, they must be "trained" by a human operator who shows the transport where to go and how to get there. A human operator also selects the route to be used when dispatching the device on it assignment. Still, once instructed, the device makes its way along its route using only its vision system for guidance.

This use of a vision system rather than a guide line is much closer operation to that of proposed autonomous cars than that of the Amazon stock robots, and it suggests ways in which autonomous cars might first come into public use. Part of the software system that monitors and manages these autonomous transport devices provides the human users with information on the fleet, showing when devices will be arriving at the pre-defined stopping points along their routes. It's rather like the announcements on a subway platform telling riders which trains are coming in when. In a manufacturing operation such information allows workers to anticipate their next stock delivery and prepare to receive it.

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