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Kensen Shi, 17, of College Station, submitted to the Intel Science Talent Search a computer science project designed to identify collision-free paths for robots trying to maneuver safely among obstacles. A widely used method to solve such motion planning problems is the Probabilistic Roadmap Method (PRM). However, PRMs can be inefficient in certain real-world environments, a problem addressed by Kensen's novel extension to the PRM algorithm he dubbed the Lazy Toggle PRM. Kensen then analyzed the efficiency of this PRM and concluded that it is more efficient than other methods — performing best in the most difficult and complex scenarios, where it generated solutions two to four times faster than the most promising of the other methods. Motion planning problems have numerous applications in robotics, animation and video game design. Kensen attends A&M Consolidated High School, where he is president of the math club, captain of the Science Bowl team, a member of the Aggie Swim Club and school recycling director. The son of Wenjie Shi and Zhe Wang, Kensen attended piano camp last summer and has placed in many musical competitions. In his spare time, he enjoys solving Rubik's cubes.
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