Vision-Based Minimum-Time Trajectory Generation for a Quadrotor UAV

Bryan Penin (1) , Riccardo Spica (2) , Paolo Robuffo Giordano (1) , François Chaumette (1)

1 Lagadic - Visual servoing in robotics, computer vision, and augmented reality
2 Stanford University

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.

Domaines: Robotique [cs.RO]

Bryan Penin, Riccardo Spica, Paolo Robuffo Giordano, François Chaumette. Vision-Based Minimum-Time Trajectory Generation for a Quadrotor UAV. IROS 2017 - IEEE/RSJ International Conference on Intelligent Robots and Systems, Sep 2017, Vancouver, Canada. pp.6199-6206. ⟨hal-01572362⟩