Autonomous Mission Planning for Unmanned Robotics Systems

During the second half of my PhD research, I became increasingly fascinated with multi-agent drone applications, especially for military applications. Coincidentally, I had also long aspired to start my own company. Thus, while still in the midst of my PhD research, I co-founded Droneconia LLC with Matt Carlin, Scott Fish, and Ufuk Topcu, a startup to develop autonomous mission planning solutions for unmanned robotics systems. In September 2022, we rebranded to Multi AI.

In the early conception stages of Multi AI, we focused on developing autonomous mission planning algorithms to help users quickly field multiple drones at once. Some of our efforts also included the exploration of these algorithms for larger unmanned systems working in unison with manned aircraft. Without being able to go into detail, the following videos and this press release give a high-level idea.

The first video shows how our solution commands three Tello drones to execute a flipping command based on a simple voice command from a user.

The second video shows a loyal wingman simulation, where our solution autonomously plans waypoint missions for four unmanned aircraft that escort a manned aircraft. Our solution processes high-level mission objectives from the user and then computes waypoint and command primitives that the drones execute.

Though our autonomous mission planning solution enjoyed success early on, we found that our military partners were more interested in applying our multi-agent AI capabilities to large-scale fleet coordination problems — specifically, optimizing contested logistics under adversarial conditions, with wargaming as a key application domain, which ultimately led to Multi-Agent Decision-Support in Adversarial Environments.