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Home Page for Sam Ade Jacobs | Parasol Laboratory


Picture Sam Ade Jacobs
PhD Student
Algorithms & Applications Group

Parasol Laboratory url: http://parasol.tamu.edu/~sjacobs/
Department of Computer Science and Engineering email:
Texas A&M University office: 407A HRBB
College Station, TX 77843-3112 tel: (979) 847-8835
USA fax: (979) 458-0718


Sam is a PhD Candidate in the Department of Computer Science and Engineering at Texas A&M University. He is also IAMCS-KAUST (Institute of Applied Mathematics and Computational Sciences - King Abdullah University of Science and Technology) Graduate Fellow. Sam's broad research interests include high performance and data intensive computing, parallel algorithms, graph algorithms, sampling-based motion planning algorithms, and computational and data sciences. Currently, he works under the direct supervision of Prof. Nancy Amato on two interrelated research projects: Motion Planning and Standard Template Adaptive Parallel Library (STAPL). The motion planning project team develops randomized motion planning algorithms with applications in mobile robots, computational biology and graphic animations. The goal of the STAPL project is to build a framework for developing parallel programs in C++.


Sam Ade Jacobs joined Lawrence Livermore National Lab (LLNL) in April 2016. Please visit his new web page .

Advisor: Prof.Nancy Amato CV/Resume: pdf


Publications

Sam Ade Jacobs, Nancy M. Amato, "The Anatomy of a Distributed Motion Planning Roadmap," In Proc. IEEE Int. Conf. Intel. Rob. Syst. (IROS), Chicago, IL, USA, Sep 2014.
Proceedings(pdf, abstract)

Adam Fidel, Sam Ade Jacobs, Shishir Sharma, Nancy M. Amato, Lawrence Rauchwerger, "Using Load Balancing to Scalably Parallelize Sampling-Based Motion Planning Algorithms," In Proc. Int. Par. and Dist. Proc. Symp. (IPDPS), Phoenix, Arizona, USA, May 2014.
Proceedings(pdf, abstract)

Sam Ade Jacobs, "A Scalable Framework for Parallelizing Sampling-Based Motion Planning Algorithms," Ph.D. Thesis, Department of Computer Science and Engineering, Texas A&M University, May 2014.
Ph.D. Thesis(pdf, abstract)

Chinwe Ekenna, Sam Ade Jacobs, Shawna Thomas, Nancy M. Amato, "Adaptive Neighbor Connection for PRMs: A Natural Fit for Heterogeneous Environments and Parallelism," In Proc. IEEE Int. Conf. Intel. Rob. Syst. (IROS), Tokyo, Japan, Nov 2013.
Proceedings(pdf, abstract)

Cesar Rodriguez, Jory Denny, Sam Jacobs, Shawna L. Thomas, Nancy M. Amato, "Blind RRT: A Probabilistically Complete Distributed RRT," In Proc. IEEE Int. Conf. Intel. Rob. Syst. (IROS), pp. 1758 - 1765, Tokyo, Japan, Nov 2013.
Proceedings(ps, pdf, abstract)

Sam Ade Jacobs, Nicholas Stradford, Cesar Rodriguez, Shawna Thomas, Nancy M. Amato, "A Scalable Distributed RRT for Motion Planning," In Proc. IEEE Int. Conf. Robot. Autom. (ICRA), pp. 5088-5095, Karlsruhe, Germany, May 2013.
Proceedings(ps, pdf, abstract)

Adam Fidel, Sam Ade Jacobs, Shishir Sharma, Lawrence Rauchwerger, Nancy M. Amato, "Load Balancing Techniques for Scalable Parallelization of Sampling-Based Motion Planning Algorithms," Technical Report, TR13-002 , Parasol Laboratory, Department of Computer Science, Texas A&M University, Mar 2013.
Technical Report(pdf, abstract)

Troy McMahon, Sam Ade Jacobs, Bryan Boyd, Lydia Tapia, Nancy M. Amato, "Local Randomization in Neighbor Selection Improves PRM Roadmap Quality," In Proc. IEEE Int. Conf. Intel. Rob. Syst. (IROS), Vilamoura, Algarve [Portugal], Oct 2012.
Proceedings(ps, pdf, abstract)

Sam Ade Jacobs, Kasra Manavi, Juan Burgos, Jory Denny, Shawna Thomas, Nancy M. Amato, "A Scalable Method for Parallelizing Sampling-Based Motion Planning Algorithms," In Proc. IEEE Int. Conf. Robot. Autom. (ICRA), pp. 2529-2536, St. Paul, Minnesota, USA, May 2012.
Proceedings(ps, pdf, abstract)

Troy McMahon, Sam Ade Jacobs, Bryan Boyd, Lydia Tapia, Nancy M. Amato, "Evaluation of the K-closest Neighbor Selection Strategy for PRM Construction," Technical Report, TR12-001, Department of Computer Science and Engineering, Texas A&M University, Jan 2012.
Technical Report(pdf, abstract)

Sam Ade Jacobs, Nancy M. Amato, "From Days to Seconds: Scalable Parallel Algorithms for Motion Planning," In ACM Student Research Compet, Conf. on High Performance Computing Networking, Storage and Analysis Companion Proceedings, Seattle, Washington, USA, Nov 2011.
Proceedings(pdf, abstract)