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Applying Dynamic Reconfiguration in the Mobile Robotics Domain: A Case Study on Computer Vision Algorithms

机译:动态重配置在移动机器人领域中的应用:计算机视觉算法的案例研究

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Mobile robots are widely used in industrial environments and are expected to be widely available in human environments in the near future, for example, in the area of care and service robots. This article proposes an implementation for a highly customizable color recognition module based on Field Programmable Gate Array (FPGA) hardware to accomplish tasks like real-time frame processing for image streams. In comparison to a pure software solution on a CPU, an attached FPGA-based hardware accelerator enables real-time image processing and significantly reduces the required computing power of the CPU. Instead, the CPU can be used for tasks that cannot be efficiently implemented on FPGAs, for example, because of a large control overhead. We concentrate on a multirobot scenario where a group of robots follows a human team member by keeping a specific formation in order to support the human in exploration and object detection. Additionally, the robots provide a communication infrastructure to maintain a stable multihop communication network between the human and a base station recording all actions and evaluating the captured images and transmitted data. Depending on the current operating conditions, the robot system has to be able to execute a wide variety of different tasks. Since only a small number of tasks have to be executed concurrently, dynamic reconfiguration of the FPGA can be used to avoid the parallel implementation of all tasks on the FPGA. Within this context, this article discusses application fields where dynamic reconfiguration of FPGA-based coprocessors significantly reduces the CPU load and presents examples of how dynamic reconfiguration can be used in exploration.
机译:移动机器人广泛用于工业环境中,并有望在不久的将来在人类环境中广泛使用,例如在护理和服务机器人领域。本文提出了一种基于现场可编程门阵列(FPGA)硬件的高度可定制颜色识别模块的实现,以完成诸如对图像流进行实时帧处理之类的任务。与CPU上的纯软件解决方案相比,连接的基于FPGA的硬件加速器支持实时图像处理,并显着降低了CPU所需的计算能力。相反,例如,由于控制开销大,CPU可以用于无法在FPGA上有效实现的任务。我们专注于多机器人场景,其中一组机器人通过保持特定的编队跟随人类团队成员,以支持人类进行探索和物体检测。另外,机器人提供了通信基础设施,以维护人与基站之间的稳定多跳通信网络,该网络记录所有动作并评估捕获的图像和传输的数据。根据当前的操作条件,机器人系统必须能够执行各种不同的任务。由于仅需要并行执行少量任务,因此可以使用FPGA的动态重新配置来避免在FPGA上并行执行所有任务。在此背景下,本文讨论了基于FPGA的协处理器的动态重配置可显着减少CPU负载的应用领域,并提供了如何在探索中使用动态重配置的示例。

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