  This study presents a hybrid trajectory optimization method that generates a
collision-free smooth trajectory for autonomous mobile robots. The hybrid
method combines sampling-based model predictive path integral (MPPI) control
and gradient-based interior-point differential dynamic programming (IPDDP)
exploiting their advantages of exploration and smoothing. The proposed method,
called MPPI-IPDDP, consists of three steps. The first step generates a coarse
trajectory by MPPI control, the second step constructs a collision-free convex
corridor, and the third step smooths the coarse trajectory by IPDDP using the
collision-free convex corridor computed in the second step. For demonstration,
the proposed algorithm was applied to trajectory optimization for
differential-driving wheeled mobile robots and point-mass quadrotors. A
supplementary video of the simulations can be found at
https://youtu.be/-oUAt5sd9Bk.
