Given the exact parameters of the task at hand, a robot can assemble a car door or pack a box faster and more efficiently than a human, but such purpose-built machines are not suited for much else. With that in mind, the history of robotics research is marked by devising ways of giving machines more and more autonomy. To achieve that end, robots must be able to sense features of never-before-seen environments and know how to interact with them.
A system was developed that enables robots to adapt to their surroundings and solve problems they were not explicitly programmed to solve. The system uses SMORES-EP (Self-Assembling
MOdular Robot for Extreme Shapeshifting (SMORES)-Electro-Permanent modules.
Individually, each module can’t do much but roll around on wheels protruding from its cubic frame. But thanks to EP magnets on those wheels and a hinged face, modules can connect to one another and achieve more complex behaviors, pick up and integrate sensor-carrying components, and manipulate metal objects. The system can make sense of objects in its environment and use them to complete a given task, such as searching the drawers of a filing cabinet.
Modular robots can have trouble dealing with crossing gaps or climbing stairs or ledges because they don’t scale well beyond a handful of individual modules. Rather than trying to find a way for the robot to handle obstacles like these, the researchers decided to teach the robot to modify its environment by giving it access to blocks and ramps that it could (autonomously) use to make obstacles easier to traverse.
This behavior is completely autonomous. The system is given a high-level task to accomplish, and the ramps and blocks are placed in the environment for it to use if it decides that they’d come in handy, but it doesn’t have explicit instructions about what to do every time.
While the objects that the SMORES-EP modules use to complete their tasks are currently labeled with markers to make them easier to find and recognize, the ultimate goal of the project is to enable robots to use whatever is at hand to get the job done.
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