We develop a system architecture for a large swarm of miniature quadcopters (Crazyflie 2.0). We investigate onboard planning, control, state estimation, communications, and a method for motion-capture localization using identical marker arrangements. We validate the system with a 49-vehicle formation flight.View Project
We investigate using crowdsourcing and online multiplayer games to develop novel and complex methods for multirobot control policies for collective tasks. By collecting data and applying learning techniques, we will create an ensemble of diverse controllers, that when used together, can solve a complex task.View Project
We investigate algorithms for mobile robotic cameras to maximize the visual coverage of multiple moving targets in dynamic environments including obstacles. This approach has a variety of applications, including for surveillance, sports events, training, and documentation of endangered animals.View Project
We develop both a theoretical framework and empirical models for extended autonomy in multirobot teams. Long-duration deployments require replenished resources, such as batteries and sensors. Our framework deals with both predicting when those resources will be needed, as well as ensuring that they are delivered in a timely manner to reduce robot down-time.View Project
Traditional single-robot algorithms tend to be slow if applied to groups of robots due to the increased dimensionality of the state space. We investigate planning algorithms which can be used or updated online for large groups of robots.
Fast planning is required in many applications in robotics, including robots for warehouses and manufacturing, construction tasks, and formation control.View Project
Mixed Reality can be a valuable tool for research and development in robotics. Specifically, our approach reduces the gap between simulation and implementation, and can eliminate safety concerns with human-robot interaction.View Project
Development of a differential-drive robot platform.View Project