(Georgia Institute of Technology, 2012-10)
Kunz, Tobias; Stilman, Mike
We present a randomized configuration space
planner that enforces soft workspace task constraints. A soft
task constraint allows an interval of feasible values while favoring a given exact value. Previous work only allows for enforcing
an exact value or an interval without a specific preference.
Soft task constraints are a useful concept in everyday life.
For example when carrying a container of liquid we want to
keep it as close to the upright position as possible but want
to be able to tilt it slightly in order to avoid obstacles. This
paper introduces the necessary algorithms for handling such
constraints, including projection methods and useful representations of everyday constraints. Our algorithms are evaluated
on a series of simulated benchmark problems and shown to
yield significant improvement in constraint satisfaction.