New robotic navigation method could speed up last-mile delivery

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MIT has developed a new navigation method that enables robots to locate front doors, an innovation that could help speed up autonomous last-mile delivery.

Standard approaches for robotic navigation require areas to be mapped in advance and use of algorithms to guide a robot toward a specific goal or GPS coordinate on a map.

However, this latest method enables a robot to use clues in its environment to plan out a route to its destination, which can be described in general semantic terms, such as ‘front door’ or ‘garage’, rather than as coordinates on a map.

For example, if a robot is instructed to deliver a package to someone’s front door, it might start on the road and see a driveway, which it has been trained to recognise as likely to lead toward a path, which in turn is likely to lead to the front door.

According to Michael Everett, a graduate student in MIT’s department of mechanical engineering, the new technique “can greatly reduce the time a robot spends exploring a property before identifying its target, and it doesn’t rely on maps of specific residences”.

“We wouldn’t want to have to make a map of every building that we’d need to visit,” said Everett. “With this technique, we hope to drop a robot at the end of any driveway and have it find a door.”

In recent years, researchers have worked on introducing natural, semantic language to robotic systems, training robots to recognise objects by their semantic labels, so they can visually process a door as a door, for example, and not simply as a solid, rectangular obstacle.

“Now we have an ability to give robots a sense of what things are, in real-time,” added Everett.

The new technique found the front door 189% faster than traditional navigation algorithms. Everett said the results illustrate how robots can use context to efficiently locate a goal, even in unfamiliar, unmapped environments.

“Even if a robot is delivering a package to an environment it’s never been to, there might be clues that will be the same as other places it’s seen,” said Everett. “So the world may be laid out a little differently, but there’s probably some things in common.”