  Trajectory replanning for quadrotors is essential to enable fully autonomous
flight in unknown environments. Hierarchical motion planning frameworks, which
combine path planning with path parameterization, are popular due to their time
efficiency. However, the path planning cannot properly deal with non-static
initial states of the quadrotor, which may result in non-smooth or even
dynamically infeasible trajectories. In this paper, we present an efficient
kinodynamic replanning framework by exploiting the advantageous properties of
the B-spline, which facilitates dealing with the non-static state and
guarantees safety and dynamical feasibility. Our framework starts with an
efficient B-spline-based kinodynamic (EBK) search algorithm which finds a
feasible trajectory with minimum control effort and time. To compensate for the
discretization induced by the EBK search, an elastic optimization (EO) approach
is proposed to refine the control point placement to the optimal location.
Systematic comparisons against the state-of-the-art are conducted to validate
the performance. Comprehensive onboard experiments using two different
vision-based quadrotors are carried out showing the general applicability of
the framework.
