  Many robots operating in unpredictable environments require an online path
planning algorithm that can quickly compute high quality paths. Asymptotically
optimal planners are capable of finding the optimal path, but can be slow to
converge. Local optimisation algorithms are capable of quickly improving a
solution, but are not guaranteed to converge to the optimal solution. In this
paper we develop a new way to integrate an asymptotically optimal planners with
a local optimiser. We test our approach using RRTConnect* with a short-cutting
local optimiser. Our approach results in a significant performance improvement
when compared with the state-of-the-art RRTConnect* asymptotically optimal
planner and computes paths that are 31\% faster to execute when both are given
3 seconds of planning time.
