Fast Motion Planning in Dynamic Environments with the Parallelized Z^3-Method

We present a method to plan collision free paths for robots with any number of degrees of freedom in dynamic environments. The method proved to be very ecient as it ommits a complete representation of the high dimensional search space. Its complexity is linear in the number of degrees of freedom. A preprocessing of the geometry data of the robot or the environment is not required. With the time as an additional dimension of the search space it is possible to use the method in known dynamic environments or for multiple robots sharing a common work space. The method allows ecient parallel planning of independent sub-tasks to increase its performance