Uploaded June 2015 | Updated September 2026, 1 hour ago
This talk was given by undergraduate Hannah Rae Kerner during the 8th Annual Computer Science Undergraduate Research Symposium in 2014. Hannah‘s research was supervised by Dr. Dinesh Manocha.
"Autonomous Navigation for Micro-Air Vehicles Using Reciprocal Velocity Obstacles"
Recent developments in autonomous flying vehicles, from industry drones to quadrotors, have generated considerable interest in the development of autonomous navigation and control techniques. Our goal is to develop automatic collision-avoidance algorithms that can account for physical constraints for micro-air vehicles (MAVs) in three dimensions. Our work builds on earlier work on collision avoidance based on reciprocal velocity obstacles (RVOs) for robots in two dimensions. We extend this work to handle kinematic and dynamic constraints for MAVs. We use the ArduCopter quadrotor helicopter (quadcopter) by 3D Robotics as the underlying physical agent along with MAVLink, a communications protocol for micro-air vehicles, to interface between the quadcopters and the RVO software library. We present preliminary results from our simulator and hardware integration.
Hannah Rae Kerner, originally from Charlotte, North Carolina, is completing her Bachelor of Science in computer science in three years at UNC. She will return to UNC next year to complete her Master of Science. She has interned for NASA for three years at both Langley Research Center and Goddard Space Flight Center, working on projects including the design of the Unmanned Aircraft System Airspace Operations Challenge, a NASA Centennial Challenge. This summer, she will intern for Planet Labs, an agile aerospace startup in San Francisco, working on ground station software and satellite systems. Hannah’s technical interests are air- and spacecraft systems, machine learning, and wearable computing. Her ultimate goal is to become an astronaut.
This talk was given by undergraduate Hannah Rae Kerner during the 8th Annual Computer Science Undergraduate Research Symposium in 2014. Hannah‘s research was supervised by Dr. Dinesh Manocha.
"Autonomous Navigation for Micro-Air Vehicles Using Reciprocal Velocity Obstacles"
Recent developments in autonomous flying vehicles, from industry drones to quadrotors, have generated considerable interest in the development of autonomous navigation and control techniques. Our goal is to develop automatic collision-avoidance algorithms that can account for physical constraints for micro-air vehicles (MAVs) in three dimensions. Our work builds on earlier work on collision avoidance based on reciprocal velocity obstacles (RVOs) for robots in two dimensions. We extend this work to handle kinematic and dynamic constraints for MAVs. We use the ArduCopter quadrotor helicopter (quadcopter) by 3D Robotics as the underlying physical agent along with MAVLink, a communications protocol for micro-air vehicles, to interface between the quadcopters and the RVO software library. We present preliminary results from our simulator and hardware integration.
Hannah Rae Kerner, originally from Charlotte, North Carolina, is completing her Bachelor of Science in computer science in three years at UNC. She will return to UNC next year to complete her Master of Science. She has interned for NASA for three years at both Langley Research Center and Goddard Space Flight Center, working on projects including the design of the Unmanned Aircraft System Airspace Operations Challenge, a NASA Centennial Challenge. This summer, she will intern for Planet Labs, an agile aerospace startup in San Francisco, working on ground station software and satellite systems. Hannah’s technical interests are air- and spacecraft systems, machine learning, and wearable computing. Her ultimate goal is to become an astronaut.
