A new category of mobile robots -- what Adept Technology is calling an autonomous indoor vehicle (AIV) -- uses a localization and navigation engine to enable self-driving operation in indoor plant and warehousing environments. The technology is designed to allow material handling equipment to behave as mobile robots and to enable lean manufacturing operations.
"With regard to key areas of technology differentiation, most engineers are familiar with how automated guided vehicles operate," Rush LaSelle, vice president and general manager of MobileRobots for Adept Technology, told us.
Many AGVs require beacons or magnets in the floor, so there is an up-front cost associated with modifying the facility for the use of an AGV.
But equally important is that AGVs tend to stay on a fixed path, so if it runs into congestion with other AGVs, or a worker inadvertently left a pallet on the floor, the AGV stops. One of the areas where we can differentiate our AIV technology is its ability to navigate better within the factory.
Adept's new Lynx mobile robot, a self-navigating AIV, is designed to move material from point to point in environments that may include confined passageways and dynamic and peopled locations. The Lynx system supports payloads of up to 60kg, utilizes digital maps for localization, and manages power and self-charging operations. (Source: Adept Technology)
One place this type of mobile robot could make a big impact is in order-picking applications. Companies like Amazon have miles of racking and millions of products. When a customer places an order, it could include a bowling ball from one end of the facility and a toothbrush from the other end. In such a case, an AGV would need to move on a fixed track all the way from one end of the facility (to pick up the bowling ball) to the other. "If you really think about the difference compared to AGVs," LaSelle said, "they are following a bus route, and we are operating like a point-to-point taxicab."
If you take the differentiation one level of abstraction further, Adept has spent a lot of development time on its Enterprise Manager. This software -- effectively middleware on an appliance between robots in a fleet -- would allow companies like Amazon to tell the robots what items are needed and where they need to be delivered.
We do all the management of which robot is available in the closest proximity, which has the best battery charge and is really ideal for the mission at hand. We also do the management of all the traffic between all of them and the queuing. All of that functionality is in a black box that ultimately provides customers a straight conveyance or transfer functionality from an ERP system.
Here are some use cases for manufacturing and warehousing.
Line-side fulfillment: Automating the movement of goods from a warehouse or staging area to an assembly or production line, robots would be used in place of forklifts or handcarts. Mobile platforms would use a small piece of conveyor or a robot to transfer parts or containers on to and off of the vehicle for movement around a facility.
Work piece movement: Complex and large products such as durables or automobiles tend to move linearly on assembly lines. Manufacturers are looking to use robots to move the vehicles to promote flexibility in how assemblies are routed through a plant. For example, an automobile affixed to a large AIV would be routed through cellular manufacturing areas, where either manual or automated processes would be carried out.
Replacing conveyor or overhead transports: In production facilities, parts and batches of parts are frequently moved between machining centers by conveyors or overhead monorail systems. Warehouses -- and especially order fulfillment centers like Amazon's -- must be able to move single piece cases rapidly and with great flexibility. Manufacturers and distributors are investing in cheaper, more flexible solutions for discrete movement of products from racks and storage to the dock and vice versa.
This platform looks like it's built with similar priniciples and technologies as some of the mobile medical robots and security robots we' ve covered before, but combining them in new ways.
NadineJ, Not sure I can answer your specific questions but here are key points that relate to those:
"Natural feature" navigation used to deliver goods throughout a facility. Uses sensor input to determine location within the environment.
Deployment time less than competing technologies. Users map the area of operation. Claim is that "productive operations can be implemented in as little as a fraction of a day" depending on size/complexity of layout.
After deployed, asset is capable of managing real-time changes in environment. This enables vehicle to handle "exceptions" which is key departure from traditional forms of navigation.
Technology like this can make it even easier and faster for online retailers to fill orders. It could even be used to help small retailers enter the online marketplace.
Any details on the up-front cost per sq ft associated with modifying any facility to use an AGV? What's the minimum facility size needed for this to be considered reasonable or cost effective?
One of the key concepts of this technology is its ability to map out the floor plan of the facility and and sense, learn and map its environment versus relying on beacons or magnetic strips in the floor. That feature might be useful in other vehicles but it is targeting the plant environment.
Good question Elizabeth. I too would like to have one if its being embeded or has the possibility to embed to a real vehicle. One quick question.. What sort of a distance does it carry signals for ?
Wow, this is really cool and a great application of this kind of technology and from the looks of the photo, they are quite sleek looking. And I imagine this is the kind of work that is painstaking for a human and could actually help a human worker be more efficient and do other things while the robot does the annoying part of the job. I also wonder if this kind of self-driving technology could have an application for self-driving cars?
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