As you saw at the top of the page, my name is Juan Aguilar. Call me Juan, or 'one' however you can, I am a dual enrollment student at South Texas College to be exact, a sophomore in college at the moment , and a rising senior of class of 2015 from Jimmy Carter Early College High School. I have two older sisters who are both college students at the University of Texas Pan-American; however, the name will change in 2015 the same year I graduate high school. My school is an Early college High School so by the time I graduate I should already have my associate degree in computer Science from STC. My favorite sport is Basketball, my favorite NBA team are the Houston Rockets. At my High School I am the 2014-2015 SHPE (Society of Hispanic Profesional Engineers) President, I am also the Vice-President for our Robotics Club. My educational goal is to Major in Computer Science and hopefully minor in education, cs is somewhat cloudy because I share an intrest in mechanical engineering. I'm unsure if I want to make the leap and maybe double major in engineering. I am using this experience in the REU to determine what I want to do. I however know that I for sure want to thrive toward a masters degree, and I am still unsure if I want to obtain a PHD.This summer I'll be working with Dr. Nancy Amato and Read Sandstrom . My primary mentor for my sub-project on User-Guided Path Planning for the summer, will be Read Sandstrom. For a short summary on my mentor, click Here.
Summer Work Abstract:
Motion planning, although much improved due to sampling-based planners, is yet to be completely solved: problems with narrow passages, efficiency, and a lack of robust- ness still remain. User-Guided Planning aims to address these shortcomings by providing a medium for a user to collaborate with the planning algorithm. In this paper, we develop and explore Path Steering, a user-guided technique that lets the user input an approximate path which will serve to seed a sampling- based planner. Path Steering allows the user to bias the sampler to areas of the workspace where a solution is expected to exist, thereby reducing the computation time required to generate efficient samples. Our Path Steering approach can be divided into three major steps: create, where we allow the user to create paths by using a mouse, PHANToM Haptic device, or the camera; configure, where the planner builds configurations on the user-guided path; and connect, where the local planner then attempts to connect valid configurations, and modifies invalid ones. Our approach handles the translation of workspace data into C-space data, so that the path is of use to the planner. Our approach demonstrated an improvement in roadmap and path quality, as well as a decrease in total runtime.
Abstract still in progress
For My Journals Click HereProject/Research
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