(Georgia Institute of Technology, 2007-04)
Stilman, Mike; Schamburek, Jan-Ullrich; Kuffner, James; Asfour, Tamin
This paper presents the ResolveSpatialConstraints
(RSC) algorithm for manipulation planning in a domain with
movable obstacles. Empirically we show that our algorithm
quickly generates plans for simulated articulated robots in a
highly nonlinear search space of exponential dimension. RSC
is a reverse-time search that samples future robot actions and
constrains the space of prior object displacements. To optimize
the efficiency of RSC, we identify methods for sampling object
surfaces and generating connecting paths between grasps and
placements. In addition to experimental analysis of RSC, this
paper looks into object placements and task-space motion constraints
among other unique features of the three dimensional
manipulation planning domain.