Wang, Y.; Han, Y.; Chen, J.; Wang, Z.; Zhong, Y. An FPGA-Based Hardware Low-Cost, Low-Consumption Target-Recognition and Sorting System. World Electr. Veh. J.2023, 14, 245.
Wang, Y.; Han, Y.; Chen, J.; Wang, Z.; Zhong, Y. An FPGA-Based Hardware Low-Cost, Low-Consumption Target-Recognition and Sorting System. World Electr. Veh. J. 2023, 14, 245.
Wang, Y.; Han, Y.; Chen, J.; Wang, Z.; Zhong, Y. An FPGA-Based Hardware Low-Cost, Low-Consumption Target-Recognition and Sorting System. World Electr. Veh. J.2023, 14, 245.
Wang, Y.; Han, Y.; Chen, J.; Wang, Z.; Zhong, Y. An FPGA-Based Hardware Low-Cost, Low-Consumption Target-Recognition and Sorting System. World Electr. Veh. J. 2023, 14, 245.
Abstract
In autonomous driving systems, high-speed and real-time image processing, along with object recognition, are crucial technologies. This paper builds upon the research achievements in in-dustrial item sorting systems and proposes an object recognition and sorting system for auton-omous driving. In industrial sorting lines, goods sorting robots often need to work at high speeds to efficiently sort large volumes of items. This poses a challenge to the robot's real-time vision and sorting capabilities, making it both practical and economically viable to implement a real-time and low-cost sorting system in a real-world industrial sorting line. Existing sorting systems have limitations such as high cost, high computing resource consumption, and high power consump-tion. These issues lead to the fact that existing sorting systems are typically used only in large industrial plants. In this paper, we design a high-speed, low-cost, low-resource-consumption FPGA (Field-Programmable Gate Array) based item sorting system that achieves similar perfor-mance to current mainstream sorting systems at a lower cost and consumption than existing sorting systems. The recognition part employs a morphological recognition method, which segments the image using a frame difference algorithm and then extracts the color and shape features of the items. To handle sorting, a six-degree-of-freedom robotic arm is introduced in the sorting segment. The improved cubic B-spline interpolation algorithm is employed to plan the motion trajectory and consequently control the robotic arm to execute the corresponding actions. Through a series of experiments, this system achieves an average recognition delay of 25.26ms, ensures smooth operation of the gripping motion trajectory, minimizes resource consumption, and reduces implementation costs.
Keywords
Autonomous Driving System, Product Design, Development and Prototyping; Motion and Path Planning; Computer Vision for Manufacturing
Subject
Engineering, Electrical and Electronic Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
