Designing embedded parallel systems with parallel genetic algorithms

Generic parallel genetic algorithms are developed with reference to the example of the real-time path planning problem for mobile robots. Most robot motion planners are used off-line: the planner is invoked with a model of the environment, it produces a path which is passed to the robot controller which in turn executes it. In general, the time necessary to achieve this loop is not short enough to allow the robot to move in a dynamic environment (moving obstacles). The goal is to try to reduce this time in order to be able to deal with real time path planning in dynamic environments. The authors use a method, called `Ariadne´s CLEW algorithm´, to build a global path planner based on the combination of two parallel genetic algorithms: an EXPLORE algorithm and a SEARCH algorithm. The purpose of the EXPLORE algorithm is to collect information about the environment with an increasingly fine resolution by placing landmarks in the searched space. The goal of the SEARCH algorithm is to opportunistically check if the target can be reached from any given placed landmark