SBIR Phase I: An Interactive 3D Game of Evolutionary Robotics for STEM-based Education

SBIR项目旨在激发高中和初中学生从事stem相关职业的可能性。根据国家教育统计中心的数据，有4700万学生就读于K-12, 2900万学生就读于初中或高中（6-12）。激励和吸引这些学生参与STEM是总统的关键组成部分。年代?教育创新计划？该项目将制作一款低成本的电脑游戏，旨在提高这些学生对stem相关职业的兴趣，让他们在应用数学、生物力学、神经科学和计算机科学原理的同时，参与机器人控制器和机器人身体部位的游戏和交互设计。根据NDP Group的数据，这款游戏通过互联网直接下载和主要应用商店进行销售，每年为商业游戏行业带来超过140亿美元的收益。与当地高中和大学研究人员合作，该项目将促进我们对如何平衡游戏挑战与学习回报的理解。这个SBIR项目提议为进化机器人领域的科学、技术、工程、数学（STEM）教育提供一个软件游戏产品。该项目将探索使用交互式进化算法（IEAs）来进化模拟机器人的行为。与进化机器人和进化算法方面的专家合作，项目团队将衡量使用IEAs与非交互式简单遗传算法和直接控制器编程相比的有效性。在IEA中，用户通过用户演示来影响演进方向。这种方法可以通过搜索空间显著减少进化时间，并为进化机器人提供更实际的方法，在设计和仿真过程中不断吸引学生用户。该项目还将研究在进化过程中使用脚手架来物理支持机器人。随着时间的推移，物理支撑被移除，随着机器人的进化，任务的难度逐渐增加，直到机器人可以独立行走或奔跑。

The SBIR project aims is to excite high school and middle school children about the possibility of working in a STEM-related career. According to the National Center for Education Statistics there are 47 million students enrolled in K-12, with 29 million in middle or high school (6-12). Inspiring and engaging these students in STEM is a key component of the President?s ?Educate to Innovate Initiative?. This project will produce a low-cost computer game designed to heighten interest in STEM-related careers among these students by engaging them in game play and interactive design of robotic controllers and robot body-parts while they apply principles of mathematics, biomechanics, neuroscience and computer science. With distribution through direct internet download and through major app stores, this product taps into the commercial gaming industry with revenues of over $14B annually according to the NDP Group. Partnering with local high schools and university researchers, the project will advance our understanding of how to balance the challenge of gaming with the rewards of learning.This SBIR project proposes to deliver a software game product for Science, Technology, Engineering, Mathematics (STEM) education in the area of evolutionary robotics. The project will explore the use of Interactive Evolutionary Algorithms (IEAs) to evolve the behavior of simulated robots. In collaboration with experts in evolutionary robotics and evolutionary algorithms, the project team will measure the effectiveness of using IEAs as compared to non-interactive simple genetic algorithms and direct controller programming. With an IEA the user influences the direction of evolution through user demonstration. This method can significantly reduce evolutionary time through the search space and provides a more hands-on approach to evolutionary robotics, continually engaging the student user during the design and simulation process. The project will also investigate the use of scaffolding to physically support the robot during the evolutionary process. The physical supports are removed over evolutionary time, gradually increasing the difficulty of the task as the robot evolves, until the robot can walk or run unassisted.