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Motivated by what is required for real-time path planning, the paper startsout by presenting sRMPD, a new recursive "local" planner founded on the keynotion that, unless made necessary by an obstacle, there must be no deviationfrom the shortest path between any two points, which would normally be astraight line path in the configuration space. Subsequently, we increase thepower of sRMPD by using it as a "connect" subroutine call in a higher-levelsampling-based algorithm mRMPD that is inspired by multi-RRT. As a consequence,mRMPD spawns a larger number of space exploring trees in regions of theconfiguration space that are characterized by a higher density of obstacles.The overall effect is a hybrid tree growing strategy with a trade-off betweenrandom exploration as made possible by multi-RRT based logic and immediateexploitation of opportunities to connect two states as made possible by sRMPD.The mRMPD planner can be biased with regard to this trade-off for solvingdifferent kinds of planning problems efficiently. Based on the test cases wehave run, our experiments show that mRMPD can reduce planning time by up to 80%compared to basic RRT.

RMPD - A Recursive Mid-Point Displacement Algorithm for Path Planning