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CUAS Videos

The following videos demonstrate specific aspects of the research performed within the CUAS project.

The video above shows some recent experimentation with our delegation and planning framework. A ground operator interacts with two micro-aerial vehicles to surveil an area by delegating cells to individual micro-aerial vehicles. A distributed temporal planner is then used to determine the task and motion plans required by the vehicles interactively with the ongoing delegation. The mission is autonomous from take-off to landing and uses a Vicon real-time tracking system for localization. The video is related to CUAS topics 1-4.

The video above shows some recent experimentation with simultaneous motion planning and obstacle avoidance. It depicts real-time plan repair based on dynamic creation of no-fly zones such as that required for a person walking into an operational area. The system continually replans motion paths using a 3D map based on input from a depth camera. The flights are autonomous and use a Vicon real-time tracking system for localization. The video is related to CUAS topic 5.

The video above shows some recent experimentation with virtual leashing of a micro-aerial vehicle to a person. The idea is that the micro-aerial vehicle passively follows an emergency rescuer around until it is needed to actively execute mission tasks required by the rescuer. Initial experimentation has been done indoors. The flight is autonomous and uses a Vicon real-time tracking system for localization. The video is related to CUAS topics 5 and 7.

The video above shows some recent experimentation with interface functionality using video see-through technology. Micro-aerial vehicles are difficult to see when flying at a distance. The idea here is to use augmented reality with iPad-like devices to enhance a ground operator's operational viewpoints of mission environments. The Vicon real-time system is used for localizing the tablet, the head and the UAV. The video is related to CUAS topic 6.

The video above shows some recent experimentation with visual detection and tracking both indoors and outdoors. A combination of image tracking algorithms augmented with probabilistic modeling of kinematics with PHD filters is used to make the task of target re-identification more robust. The video is related to CUAS topic 7.


Page responsible: Patrick Doherty
Last updated: 2015-04-28