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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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Title: Heterogeneous Parallelism in Sampling-based Motion Planning
Committee:
Dr. Wills, Advisor
Dr. Tsiotras, Co-Advisor
Dr. Hutchinson, Chair
Dr. Vela
Abstract: The objective of the proposed research is to maximize the parallelism extracted from sampling-based motion planning algorithms on heterogeneous architectures by making explicit the interaction between fundamental algorithmic constraints and available computing resources. Motion planning plays a central role in autonomous robotic systems, enabling navigation of previously unseen environments in a safe and efficient manner. Sampling-based methods are the de facto choice for most applications, given their incremental anytime improvement, graceful handling of complex constraints, and efficient exploration of high dimensional configuration spaces. As new computer architectures emerge delivering better performance and power consumption, there will be increasing opportunity to utilize such architectures to extend robotic capability. This work will systematically explore the design space of incremental motion planning algorithms on heterogeneous architectures to identify the essential control and data dependencies among subroutines, barriers to dynamic compute allocation based on program performance, and cost-benefit analysis of path and data structure optimizations.
