论文标题
Clipbot：一种教育，身体受损的机器人，学会通过遗传算法优化行走
ClipBot: an educational, physically impaired robot that learns to walk via genetic algorithm optimization
论文作者
论文摘要
教育机器人允许实验机械，电子和信息学的各种原则。在这里，我们提出了一个低成本的，自己动手的机器人，其骨骼由两个纸夹制成。 Arduino纳米微控制器会使两个移动纸夹的伺服电机。但是，这种机械配置赋予了运动的物理障碍。这创造了需求并允许尝试人工智能方法克服硬件限制。我们报告了由瑞士基金会Schweizer Jugend Forscht（www.sjf.ch）组织的学习周“迷人信息学”期间使用该机器人的经验。高中的学生被要求实施一种遗传算法，以优化机器人的运动，直到学会走路为止。这种方法使机器人能够使用少于20个迭代来学习电动机致动方案，从而在向前方向上产生直运动。
Educational robots allow experimenting with a variety of principles from mechanics, electronics, and informatics. Here we propose ClipBot, a low-cost, do-it-yourself, robot whose skeleton is made of two paper clips. An Arduino nano microcontroller actuates two servo motors that move the paper clips. However, such mechanical configuration confers physical impairments to movement. This creates the need for and allows experimenting with artificial intelligence methods to overcome hardware limitations. We report our experience in the usage of this robot during the study week 'fascinating informatics', organized by the Swiss Foundation Schweizer Jugend Forscht (www.sjf.ch). Students at the high school level were asked to implement a genetic algorithm to optimize the movements of the robot until it learned to walk. Such a methodology allowed the robot to learn the motor actuation scheme yielding straight movement in the forward direction using less than 20 iterations.
