One of the biggest challenges facing robots is unpredictable environments. Robots excel in a factory or laboratory setting. They thrive when conditions are controlled and consistent. They perform their programmed tasks to a T with speed, efficiency, and consistency that no human can match. Of course, machines wilt once things get a little less predictable. Environments where things cannot be the exact same all the time – i.e. the real world – present challenges for autonomous robots.
So how do you fix this problem? One option is teach robots how to adapt. Another option is to teach robots to manipulate the environment that they’re in to better suit them.
If you can’t adapt, manipulate
It’s difficult to make a robot that can adapt to its environment. It’s much easier to develop a robot that can change its surroundings than to make a robot that can change in response to its surroundings.
Researchers from the University of Pennsylvania’s ModLab are working on a modular robot that can manipulate its environment in order to carry out a specified function.
The researchers give the SMORES-EP robot tasks that it cannot complete given environmental factors. The robot must try to locate items in a filing cabinet and cross a gap between two tables.
While the SMORES-EP robot can search the bottom drawer of the filing cabinet, it can’t search any higher. So, the robot instead uses a ramp to modify the environment, which allows it to search the next drawer and locate the the items.
Similarly, the robot can’t cross the gap, so it manipulates the environment and builds a bridge, allowing it to reach its goal.
Does this benefit industrial robots?
It’s easy to see the advantages of a robot that can change its surroundings. Robots that are used for search and rescue, exploration robots such as the Mars rover, or any other mobile robots need to be able to adjust to unforeseen variables.
While this ability would greatly benefit mobile robots, it seems less useful for factory robots, however. In fact, one of the things that makes industrial robots so great is their predictability.
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