Ms. Carol Cheung Profile

Carol Cheung

at iRobot Corp

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Publications (2)

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Proceedings Article | 29 April 2009 Paper

Integrated long-range UAV/UGV collaborative target tracking

Mark Moseley, Benjamin Grocholsky, Carol Cheung, Sanjiv Singh

Proceedings Volume 7332, 733204 (2009) https://doi.org/10.1117/12.820289

KEYWORDS: Unmanned aerial vehicles, Video, Optical tracking, Telecommunications, Robots, Cameras, Sensors, Target detection, Data communications, Detection and tracking algorithms

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Coordinated operations between unmanned air and ground assets allow leveraging of multi-domain sensing and increase opportunities for improving line of sight communications. While numerous military missions would benefit from coordinated UAV-UGV operations, foundational capabilities that integrate stove-piped tactical systems and share available sensor data are required and not yet available. iRobot, AeroVironment, and Carnegie Mellon University are working together, partially SBIR-funded through ARDEC's small unit network lethality initiative, to develop collaborative capabilities for surveillance, targeting, and improved communications based on PackBot UGV and Raven UAV platforms. We integrate newly available technologies into computational, vision, and communications payloads and develop sensing algorithms to support vision-based target tracking. We first simulated and then applied onto real tactical platforms an implementation of Decentralized Data Fusion, a novel technique for fusing track estimates from PackBot and Raven platforms for a moving target in an open environment. In addition, system integration with AeroVironment's Digital Data Link onto both air and ground platforms has extended our capabilities in communications range to operate the PackBot as well as in increased video and data throughput. The system is brought together through a unified Operator Control Unit (OCU) for the PackBot and Raven that provides simultaneous waypoint navigation and traditional teleoperation. We also present several recent capability accomplishments toward PackBot-Raven coordinated operations, including single OCU display design and operation, early target track results, and Digital Data Link integration efforts, as well as our near-term capability goals.

Proceedings Article | 22 April 2008 Paper

UAV-UGV collaboration with a PackBot UGV and Raven SUAV for pursuit and tracking of a dynamic target

Carol Cheung, Benjamin Grocholsky

Proceedings Volume 6962, 696216 (2008) https://doi.org/10.1117/12.777188

KEYWORDS: Unmanned aerial vehicles, Sensors, Unmanned vehicles, Satellite imaging, Earth observing sensors, Satellites, Navigation systems, Cameras, Video, Unmanned systems

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Fielded military unmanned systems are currently extending the reach of the U.S. forces in surveillance and reconnaissance missions. Providing long-range eyes on enemy operations, unmanned aerial vehicles (UAVs), such as the AeroVironment Raven, have proven themselves indispensable without risking soldiers' lives. Meanwhile, unmanned ground vehicles (UGVs), such as the iRobot PackBot, are quickly joining ranks in Explosive Ordnance Disposal (EOD) missions to identify and dispose of ordnance or to clear roads and buildings. UAV-UGV collaboration and the benefit of force multiplication is increasingly more tangible. iRobot Corporation and CMU Robotics Institute are developing the capability to simultaneously control the Raven small UAV (SUAV) and PackBot UGV from a single operator control unit (OCU) via waypoint navigation. Techniques to support autonomous collaboration for pursuing and tracking a dismounted soldier will be developed and integrated on a Raven-PackBot team. The Raven will survey an area and geolocate an operator-selected target. The Raven will share this target location with the PackBot and together they will collaboratively pursue the target intelligently to maintain track on the target. We will accomplish this goal by implementing a decentralized control and data fusion software architecture. The PackBot will be equipped with on-board waypoint navigation algorithms, a Navigator Payload containing a stereo-vision system, GPS, and a high-accuracy IMU. The Raven will have two on-board cameras, a side-looking and a forward-looking optical camera. The Supervisor OCU will act as the central mission planner, allowing the operator to monitor mission events and override vehicle tasks.

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