  We focus on a replanning scenario for quadrotors where considering time
efficiency, non-static initial state and dynamical feasibility is of great
significance. We propose a real-time B-spline based kinodynamic (RBK) search
algorithm, which transforms a position-only shortest path search (such as A*
and Dijkstra) into an efficient kinodynamic search, by exploring the properties
of B-spline parameterization. The RBK search is greedy and produces a
dynamically feasible time-parameterized trajectory efficiently, which
facilitates non-static initial state of the quadrotor. To cope with the
limitation of the greedy search and the discretization induced by a grid
structure, we adopt an elastic optimization (EO) approach as a
post-optimization process, to refine the control point placement provided by
the RBK search. The EO approach finds the optimal control point placement
inside an expanded elastic tube which represents the free space, by solving a
Quadratically Constrained Quadratic Programming (QCQP) problem. We design a
receding horizon replanner based on the local control property of B-spline. A
systematic comparison of our method against two state-of-the-art methods is
provided. We integrate our replanning system with a monocular vision-based
quadrotor and validate our performance onboard.
