Home /Research /Vision-based minimum-time trajectory generation for a quadrotor UAV
OTHER

Vision-based minimum-time trajectory generation for a quadrotor UAV

Bryan Penin, Riccardo Spica, Paolo Robuffo Giordano, François Chaumette

Year
2017
Citations
50

Abstract

In this paper, we address the problem of using a camera with limited field of view for controlling the motion of a quadrotor in aggressive flight regimes. We present a minimum time trajectory planning method that guarantees visibility of the image features while allowing the robot to undertake aggressive motions for which the usual near-hovering assumption is violated. We exploit differential flatness and B-Splines to parametrize the system trajectories in terms of a finite number of control points, which can then be optimized by Sequential Quadratic Programming (SQP). The control strategy is similar to a Receding Horizon Control (RHC) approach for modifying online the reference trajectory in order to account for noise, disturbances and any non-modeled effect. The algorithm is validated in a physically realistic simulation environment.

Keywords

TrajectorySequential quadratic programmingControl theory (sociology)Computer scienceQuadratic programmingRobotTrajectory optimizationMotion planningComputer visionOptimal control

Related papers

Browse all OTHER papers