Researchers create a trajectory-planning system that enables drones working together in the same airspace to always choose a safe path forward. When multiple drones are working together in the same airspace, perhaps spraying pesticide over a field of corn, there’s a risk they might crash into eac
MIT researchers have developed Robust MADER, an updated multiagent trajectory-planner system that helps prevent drone collisions by generating collision-free trajectories even when communications between drones are delayed. The algorithm incorporates a delay-check step, during which a drone waits a specific amount of time before committing to a new, optimized trajectory.
But when the team tested the system on real drones, they found that if a drone doesn’t have up-to-date information on the trajectories of its partners, it might inadvertently select a path that results in a collision. The researchers revamped their system and are now rolling out Robust MADER, a multiagent trajectory planner that generates collision-free trajectories even when communications between agents are delayed.
The algorithm incorporates a delay-check step during which a drone waits a specific amount of time before it commits to a new, optimized trajectory. If it receives additional trajectory information from fellow drones during the delay period, it might abandon its new trajectory and start the optimization process over again.
Kondo wrote the paper with Jesus Tordesillas, a postdoc; Parker C. Lusk, a graduate student; Reinaldo Figueroa, Juan Rached, and Joseph Merkel, MIT undergraduates; and senior author Jonathan P. How, the Richard C. Maclaurin Professor of Aeronautics and Astronautics, a principal investigator in the Laboratory for Information and Decision Systems , and a member of the MIT-IBM Watson AI Lab. The research will be presented at the International Conference on Robots and Automation.
Robust MADER prevents such collisions because each agent has two trajectories available. It keeps one trajectory that it knows is safe, which it has already checked for potential collisions. While following that original trajectory, the drone optimizes a new trajectory but does not commit to the new trajectory until it completes a delay-check step.
The researchers also built six drones and two aerial obstacles and tested Robust MADER in a multiagent flight environment. They found that, while using the original version of MADER in this environment would have resulted in seven collisions, Robust MADER did not cause a single crash in any of the hardware experiments.
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