MIT Creates Algorithm Which Will Help Drones To Navigate Between Moving Obstacles

We already have technology that prevents robots and drones from striking against fixed obstacles, but avoiding collisions with other moving objects is a much greater challenge. But thanks to a control algorithm, MIT has solved this equation.

Researchers at MIT announced a control algorithm that helps robots to avoid embarrassing encounters with moving objects, including other robots.

MIT Creates Algorithm Which Will Help Drones To Navigate Between Moving Obstacles

Planning algorithms for robot teams can be centralized, where each computer makes decisions for the entire team, or decentralized, where each robot makes his own decisions.

The latter approach is much better in incorporating observations of locations, but it is also much more challenging since each robot must essentially guess what others are doing.

The new MIT algorithm assumes a decentralized approach and factors that not only fixed obstacles such as those in motion. Each robot uses observations to measure a region without obstacles in its immediate context.

Then it passes such a map to its nearest neighbors. When a robot receives a map from a neighbor, it calculates the intersection map with its own and follows the changes to its peers.

Since each robot communicates only with its immediate neighbors, the band rate required for communication is reduced significantly, particularly when there are many robots. And each robot ends up with a map that reflects all the obstacles the team detected.

The algorithm considers moving obstacles to include time as a fourth dimension in the mapping. This dimension describes how a three-dimensional map should be changed to accommodate the change of location of the obstacle in a range of seconds.

In simulations with drones, the algorithm achieved the same flight plan as a centralized version but allowed small variations as required.

Daniela L. Rus, a professor in the Department of Electrical Engineering and computer scientist and director of the Computer Science and Artificial Intelligence Laboratory, said, “It’s a really exciting result by combining many challenging objectives”.

Each robot updates its map several times per second, calculating the trajectory to maximize local and global goals. For similar environments where humans and robots work together, researchers are also testing a version of its algorithm for robots equipped with wheels whose goal is to collectively carry an object over a room where humans are also moving.

The researchers will present their algorithm next month at the International Conference on Robotics and Automation, which takes place in May in Stockholm, Sweden.


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