Quadrocopter ball juggling

This paper presents a method allowing a quadrocopter with a rigidly attached racket to hit a ball towards a target. An algorithm is developed to generate an open loop trajectory guiding the vehicle to a predicted impact point - the prediction is done by integrating forward the current position and velocity estimates from a Kalman filter. By examining the ball and vehicle trajectories before and after impact, the system estimates the ball's drag coefficient, the racket's coefficient of restitution and an aiming bias. These estimates are then fed back into the system's aiming algorithm to improve future performance. The algorithms are implemented for three different experiments: a single quadrocopter returning balls thrown by a human; two quadrocopters co-operatively juggling a ball back-and-forth; and a single quadrocopter attempting to juggle a ball on its own. Performance is demonstrated in the Flying Machine Arena at the ETH Zurich.

Authors

• Mark W. Mueller
• Sergei Lupashin
• Raffaello D'Andrea

Keywords

• Trajectory
• Vehicles
• Mathematical model
• Equations
• Acceleration
• Vehicle dynamics
• Robots
• Kalman Filter
• Drag Coefficient
• ETH Zurich
• Impact Point
• Large Distances
• Linear System
• Equations Of Motion
• Position Error
• Motion Capture
• Tracking Error
• Mechanical Energy
• Angular Speed
• Pitch Angle
• Roll Angle
• Euler Angles
• Motor Commands
• Angular Acceleration
• Inertial Frame
• Single Vehicle
• Trajectory Generation
• Input Saturation
• Ball Speed
• Ball Velocity
• Popular Research Topics
• Angular Velocity
• Retroreflective