(This is Part 2 of an ongoing interview with Professor Davide Scaramuzza, the head of the University of Zurich’s Robotics and Perception Group.)

What we know as a society is that collaboration and cooperation are better than individual entities operating alone. This is also true for a team of collaborating ground and aerial robots.

Ground robots have a limited view, they are constrained to move on the ground. But they can carry heavy payloads, such as sensors and batteries, and, thus, they have longer endurance. An aerial robot meanwhile can provide an overhead view of the environment, and can overcome all the obstacles of ground robots, but has limited payload and endurance.

If we combine them together, we get a system that benefits from the advantages of these two robots. So, the idea we are currently researching about is how to use an aerial robot as an external flying camera to provide the ground robot with an overview of the environment, to help it better plan its actions.

In one of our research publications, the drone searches for a victim and builds a map of the environment that a rover then utilises to plan the shortest path to the victim and deliver a first-aid kit.

The aerial robot also builds a semantic map, where each obstacle is labeled as fixed or removable. Then, the ground robot computes the shortest path to the victim, taking into account the time to remove and place an obstacle somewhere else. These robots communicate through Wi-Fi. Since the ground robot can carry heavier payloads, most computation is done on the PC onboard the ground robot.

This is a fascinating discussion. Scaramuzza is one of the researchers who makes Switzerland such a drone powerhouse. This article also touches on a number of other research projects including agility and event-based vision where the goal is to build sensors systems that allow and drone to respond as fast as a bird.
Interesting to look at this in combination with the recent Ford patent announcement where again the idea is to use an aerial drone to scout for an autonomous vehicle.



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