eLIAN: Enhanced Algorithm for Angle-constrained Path Finding
  Problem of finding 2D paths of special shape, e.g. paths comprised of line
segments having the property that the angle between any two consecutive
segments does not exceed the predefined threshold, is considered in the paper.
This problem is harder to solve than the one when shortest paths of any shape
are sought, since the planer's search space is substantially bigger as multiple
search nodes corresponding to the same location need to be considered. One way
to reduce the search effort is to fix the length of the path's segment and to
prune the nodes that violate the imposed constraint. This leads to
incompleteness and to the sensitivity of the 's performance to chosen parameter
value. In this work we introduce a novel technique that reduces this
sensitivity by automatically adjusting the length of the path's segment
on-the-fly, e.g. during the search. Embedding this technique into the known
grid-based angle-constrained path finding algorithm - LIAN, leads to notable
increase of the planner's effectiveness, e.g. success rate, while keeping
efficiency, e.g. runtime, overhead at reasonable level. Experimental evaluation
shows that LIAN with the suggested enhancements, dubbed eLIAN, solves up to
20\% of tasks more compared to the predecessor. Meanwhile, the solution quality
of eLIAN is nearly the same as the one of LIAN.
