This paper presents a trajectory planner and a control architecture capable of guiding a quadrotor biplane tailsitter
(QRBP) through obstacle cluttered environments. The trajectory planner is formulated as an optimization problem
that uses a differentially flat, point-mass model of a QRBP that considers wake effects on the aerodynamic forces
generated during transition. Obstacle avoidance is realized as a state constraint in the optimization problem that defines
’no-flight zones’ or regions where the QRBP cannot enter based on obstacle size and safety clearance requirements.
The 6DOF control architecture is designed as a set of cascaded dynamic inversion controllers that use the aerodynamic
feedforward signals produced by the trajectory planner to complete the inversion in the outer loop. To show the
effectiveness of the obstacle avoidance path planning methodology, time-optimal trajectories are generated for two
flight missions (the hover to forward flight and vice versa) through cluttered environments. The control architecture is
validated on these two cases using a high fidelity flight dynamics simulation of a QRBP. The computational efficiency
of the trajectory planner and the tracking performance of the control architecture are then empirically validated.
Reference
Proceedings of the Vertical Flight Society 78th Annual Forum, Fort Worth, Texas, USA, May 10-12, 2022.