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Design and implementation of fuzzy-logic based obstacle-avoidance and target-reaching algorithms on NI's embedded-FPGA robotic platform

机译:基于模糊逻辑基于障碍物的避免和目标到达算法的设计与实现NI嵌入式FPGA机器人平台

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In this work we design, simulate and implement two fuzzy-logic based algorithms for mobile robots: one for obstacle avoidance, and another one with the combined objective of avoiding obstacles and as well as reaching a pre-defined target point in an unknown environment. The hardware used in this project is the National Instruments (NI)'s embedded robotic platform which houses the SBRIO (Single-board Reconfigurable Input-Output) that includes a powerful real-time controller, and a field programmable gate array (FPGA). For obstacle avoidance the robot has only one rotating ultrasonic sensor on the front side. The software is implemented using high-level Lab VIEW modules for embedded FPGA and real-time programming. Results show the key advantages of this new approach which is its accuracy, simplicity and quicker reaction to sudden changes especially when the robot is moving in an unstructured environment. This is due to the fact that the approach accounts for the size and shape of the robot and generates the speed of motion proportional to the distance from the obstacle.
机译:在这项工作中,我们设计,模拟和实施一种基于移动机器人的模糊逻辑算法:一个用于避免避免的一个,以及另一个具有避免障碍的组合目标,以及在未知环境中达到预定义目标点。该项目中使用的硬件是国家仪器(NI)的嵌入式机器人平台,其包括一个包括强大的实时控制器的SBRIO(单板可重新配置输入输出)和现场可编程门阵列(FPGA)。对于避免障碍物,机器人在前侧只有一个旋转超声波传感器。该软件是使用用于嵌入式FPGA和实时编程的高级实验室视图模块来实现。结果表明,这种新方法的关键优势,这是其准确性,简单性和对突然变化的反应,特别是当机器人在非结构化环境中移动时。这是由于该方法占机器人的尺寸和形状并产生与障碍物的距离成比例的运动速度。

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