Deterministic Path Planning for Non-Holonomic Vehicles Including Friction and Steer Rate Limitations
Path planning algorithms have evolved during
decades to become computationally less expensive and optimal.
In this paper a deterministic approach is used to find a path
near to the shortest path using motion primitives. The motion
primitives are constructed using a non-holonomic vehicle model.
The physical model enables the algorithm to use a friction map
and calculate paths with lower lateral slip forces. Furthermore
the algorithm takes into account the steer rate using steer
angles assigned for motion primitives. The algorithm is an A*
based search method along with a heuristic to find a near
optimal solution. The performance and calculation time of the
algorithm is tunable by adjusting motion primitive size and
discretization steps. In order to compare the algorithm output
to optimal solution a direct multiple shooting method is used.
The algorithm is simulated in different scenarios that shows the
properties of the algorithm. The results attained from search
method is compared with optimal solution in two different
test scenarios and the comparison shows consistency of search
method to the optimal solution.
Mahdi Morsali, Fatemeh Mohseni and Erik Frisk
2017
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