Robots have learned to grab and move objects with ease

Automating warehouse tasks can be tricky. Many actions that are natural for people, in fact

are quite a challenge forrobots. For example, deciding where and how to get different types of objects. It is also important to further coordinate the movements of the shoulders, arms and wrists, which are necessary to move each of them from one place to another. In addition, the movements of the robots are sharper - this increases the risk of damage to both objects and robots.

“Warehouses are still serviced mainlyhumans, because robots still have a very difficult time reliably capturing many different objects, explains Ken Goldberg, senior author of the study. - On an automotive assembly line, the same movement is repeated over and over, so it can be automated. But in the warehouse, all orders are different. "

Video demonstrating the work of a warehouse robotic arm with movement before and after the application of a deep neural network. Credit: Ichnowski et al.

In an earlier work, Goldberg and ScholarJeffrey Ichnowski at UC Berkeley has created a grasp-optimized motion planner. However, the engineers failed to make the movements smooth. Although the software parameters were adjusted to create exactly this, the calculations took about half an hour on average.

In a new study by Goldberg and Ichnowski inCollaboration with UC Berkeley graduate student Yahav Avigal and student Vishal Satish significantly accelerated the computation time of the motion planner by integrating a neural network with deep learning.

Neural networks allow the robot to learn fromexamples. Later, the robot can often generalize similar objects and movements. However, these approximations are not always accurate enough. Goldberg and Ichnowski found that the approximation generated by the neural network can then be optimized using a dedicated scheduler. By combining a neural network with a motion planner, the team reduced the average computation time from 29 seconds to 80 milliseconds.

The study authors are confident that thanks to thisand other advances, robots will soon be able to help warehouse workers. “This is a great new opportunity for robots to support humans,” concludes Goldberg.

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