The conventional picking robots suffered from low picking throughput due to a large amount of computation of the object-pose-estimation algorithm which is called iterative-closest-point (ICP) algorithm. This article presents an field-programmable gate array (FPGA)-based ICP accelerator, which achieves 11.7-times-faster object-pose estimation by a picking robot compared with the state-of-the-art technique based on K-D-tree <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</i> -nearest neighbor (NN) search and four-core CPU. To accelerate the ICP, both algorithm-level and hardware-level techniques have been proposed and developed. The former is a hierarchical-graph-based <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</i> -NN search enabling simultaneous acquisition of plural neighboring points. The latter is a sorting-network-based circuit implemented on an system on a chip (SoC)-FPGA. In addition, dynamic structural reconfiguration between the two key functionalities (graph generation and nearest neighbor search) is explored by utilizing the partial reconfiguration capability of FPGA to save the required hardware resource. Experiments of the proposed FPGA-based ICP accelerator using Amazon Picking Challenge data sets have confirmed that the object-pose estimation by ICP takes only 0.72 s at the power consumption of 4.2 W.

Atsutake Kosuge

Keisuke Yamamoto

Yukinori Akamine

Takashi Oshima

IEEE Transactions on Industrial Electronics

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 每月出版一次。其范围包括电子、控制和通信、仪器仪表和计算智能的应用，以增强工业和制造系统和流程。包括电力电子和驱动控制技术、系统控制和信号处理、故障检测和诊断、电力系统、仪器仪表、测量和测试、建模和仿真、运动控制、机器人、传感器和执行器、神经网络的实现、模糊逻辑、工业系统、工厂自动化、通信和计算机网络中的人工智能。

The IEEE Transactions on Industrial Electronics is a monthly journal that covers the application of electronics, control and communication, instrumentation, and computational intelligence to enhance industrial and manufacturing systems and processes. The journal includes topics such as power electronics and drive control technologies, system control and signal processing, fault detection and diagnosis, power systems, instrumentation, measurement and testing, modeling and simulation, motion control, robotics, sensors and actuators, implementation of neural networks, fuzzy logic, industrial systems, factory automation, and artificial intelligence in communication and computer networks.

《IEEE Transactions on Industrial Electronics》是一本每月出版的期刊，涵盖电子、控制与通信、仪器仪表及计算智能在工业和制造系统中的应用。期刊内容包括电力电子与驱动控制技术、系统控制与信号处理、故障检测与诊断、电力系统、仪器仪表、测量与测试、建模与仿真、运动控制、机器人、传感器与执行器、神经网络实现、模糊逻辑、工业系统、工厂自动化以及通信与计算机网络中的人工智能等领域。

IEEE Trans. Ind. Electron.

An SoC-FPGA-Based Iterative-Closest-Point Accelerator Enabling Faster Picking Robots

An field-programmable gate array (FPGA)-based ICP accelerator, which achieves 11.7-times-faster object-pose estimation by a picking robot compared with the state-of-the-art technique based on K-D-tree k-nearest neighbor (NN) search and four-core CPU.

Category	Quartile
工程技术	1
工程技术, 自动化与控制系统	1
工程技术, 工程电子与电气	1
工程技术, 仪器仪表	1

An SoC-FPGA-Based Iterative-Closest-Point Accelerator Enabling Faster Picking Robots

ivySCI AI Smartly Parses PDF, Answers Researchers' Questions, and Helps You Understand Papers in Seconds

Journal Info

Category	Quartile
INSTRUMENTS & INSTRUMENTATION	1