Our Star Student Project objective is to further investigate improvements to RRT by exploiting speedup from parallel computation. Some results have been obtained in that direction. Nevertheless, the existing study considers mainly shared-memory architectures and small-scale parallelism, up to 16 processors. Star Student Project is interested in what can be achieved by larger scale parallelism. We focus on parallelizing RRT on distributed-memory architectures, which requires the use of the message passing interface (MPI). The idea of Star Student Project improving motion-planning performance using parallel computation is not new.
Project Support for : Ph.D/M.E/M.Tech/B.E/B.Tech/MCA/Msc/BCA/Diplomo
Department : Computer Science/ Information Technology/ Electronics
Star Student Project
Our Star Student Project objective is to further investigate improvements to RRT by exploiting speedup from parallel computation. Some results have been obtained in that direction. Nevertheless, the existing study considers mainly shared-memory architectures and small-scale parallelism, up to 16 processors. Star Student Project is interested in what can be achieved by larger scale parallelism. We focus on parallelizing RRT on distributed-memory architectures, which requires the use of the message passing interface (MPI). The idea of Star Student Project improving motion-planning performance using parallel computation is not new.