S. Sekhavat et al., MULTILEVEL PATH PLANNING FOR NONHOLONOMIC ROBOTS USING SEMIHOLONOMIC SUBSYSTEMS, The International journal of robotics research, 17(8), 1998, pp. 840-857
Citations number
26
Categorie Soggetti
Robotics & Automatic Control","Robotics & Automatic Control
We present a new and complete multilevel approach for solving path-pla
nning problems for nonholonomic robots. At the first level, a path is
found that disrespects (some of) the nonholonomic constraints. At each
of the next levels, a new path is generated by transformation of the
path generated at the previous level. The transformation is such that
more nonholonomic constraints are respected than at the previous level
. At the final level, all nonholonomic constraints are respected. We p
resent two techniques for these transformations The first, which we ca
ll the pick and link technique, repeatedly picks pieces from the given
path, and tries to replace them by more feasible ones. The second tec
hnique restricts the free configuration space to a ''tube'' around the
given path, and a road map that captures the free-space connectivity
within this tube is constructed by the probabilistic path planner From
this road map we retrieve a new, more feasible path. In the intermedi
ate levels, we plan paths for what we refer to as semiholonomic subsys
tems. Such systems are obtained by taking real (physical) systems, and
removing some of their nonholonomic constraints. In this paper we app
ly the scheme to carlike robots pulling trailers, that is, tractor-tra
iler robots. In this case, the real system is the tractor-trailer robo
t, and the ignored constraints in the semiholonomic subsystems are the
kinematic ones on the trailers. These are the constraints of rolling
without slipping, on the trailer's wheels. Experimental results are gi
ven that illustrate the time efficiency of the resulting planner. In p
articular, we show that using the multilevel scheme leads to significa
ntly better performance (in computation time and path shape) than dire
ct transformations to feasible paths.