Abstract:
In this paper we present a time efficient one step path planning
algorithm for navigating a large robotic platform in indoor
environments. The proposed strategy, based on the generation
of a novel search space [1], relies on non-uniform
density sampling of the free areas to direct the computational
resources to troubled and difficult regions, such as narrow
passages, leaving the larger open spaces sparsely populated.
A smoothing penalty is also associated to the nodes to encourage
the generation of gentle paths along the middle of
the empty spaces. Collision detection is carried out off-line
during the creation of the configuration space to speed up
the actual search for the path, which is done on-line. Results
compared to currently available path planning algorithms
such as Randomly-exploring Random Trees (RRTs)
and Probabilistic Road Maps (PRMs) proved that the proposed
approach considerably reduces the searching time and
produces smoother paths with less jagged path segments than
those from randomized planners.
