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)
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.
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.
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?
According to a study by the National Institute of Standards and Technology, one of the factors in the collapse of the original World Trade Center towers on Sept. 11, 2001, was the reduction in the yield strength of the steel reinforcement as a result of the high temperatures of the fire and the loss of thermal insulation.
Robots are getting more agile and automation systems are becoming more complex. Yet the most impressive development in robotics and automation is increased intelligence. Machines in automation are increasingly able to analyze huge amounts of data. They are often able to see, speak, even imitate patterns of human thinking. Researchers at European Automation
call this deep learning.
The promise of the Internet of Things (IoT) is that devices, gadgets, and appliances we use every day will be able to communicate with one another. This potential is not limited to household items or smartphones, but also things we find in our yard and garden, as evidenced by a recent challenge from the element14 design community.
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