RoboSAM Robot can call for human help if needed

Smart Robot can assess its situation and call a human for help when it needs assistance.

Researchers from the University of Maryland have developed RoboSAM (ROBOtic Smart Assistant for Manufacturing), an industrial robot smart enough to know when something is wrong, to pause and to call a human for help.

The new RoboSAM, based on the Baxter industrial robot platform, is able to estimate the probability it can complete a task before beginning it, and can ask a human help if necessary.

Currently, industrial robots are used mostly for high-volume, reliably repetitive tasks with unchanging, tightly proscribed parameters, such as automobile assembly lines.

These robots are custom-built and programmed specifically for the tasks at hand. While they excel in such environments, the robots have a limited ability to assess whether they can successfully complete tasks.

These robots do not know when they should stop what they are doing if things are not placed in order and this can result in a chaotic mess.

That is why industrial robots cannot be used in factories where high task reliability cannot be ensured.

RoboSAM’s abilities may provide a path forward towards smarter, more versatile industrial robots and more interesting duties for the humans who work with them.

In most situations, providing task assistance help to robots is much more cost-effective than recovering from a system shutdown.

Satyandra Gupta who led this research demonstrated RoboSAM in a “bin picking” situation. The robot needs to find a desired object in a bin of similar objects, pick it up, and deliver it to another area in a specific placement.

If the robot cannot find the part as it is “buried” within the bin, it takes pictures of its situation and calls a remotely located human for help.

The human then suggests to the robot what it should do to complete the task, such as stir the contents of the bin and then try again to locate the needed part.

Gupta believes this work is the beginning of providing a better economic model for deploying robots, especially for small and medium-sized manufacturing companies.

 

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