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首页> 外文期刊>Journal of Intelligent & Robotic Systems: Theory & Application >Vision-Based Robotic Motion Control for Non-autonomous Environment
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Vision-Based Robotic Motion Control for Non-autonomous Environment

机译:非自主环境下基于视觉的机器人运动控制

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A visual servo control system with SOPC structure is implemented on a retrofitted Mitsubishi Movemaster RV-M2 robotic system. The hardware circuit has the functions of quadrature encoder decoding, limit switch detecting, pulse width modulation (PWM) generating and CMOS image signal capturing. The software embedded in Nios II micro processor has the functions of using UART to communicate with PC, robotic inverse kinematics calculation, robotic motion control schemes, digital image processing and gobang game AI algorithms. The digital hardware circuits are designed by using Verilog language, and programs in Nios II micro processor are coded with C language. An Altera Statrix II EP2S60F672C5Es FPGA chip is adopted as the main CPU of the development board. A CMOS color image sensor with 356 × 292 pixels resolution is selected to catch the environment time-varying change for robotic vision-based servo control. The system performance is evaluated by experimental tests. A gobang game is planned to reveal the visual servo robotic motion control objective in non-autonomous environment. Here, a model-free intelligent self-organizing fuzzy control strategy is employed to design the robotic joint controller. A vision based trajectory planning algorithm is designed to calculate the desired angular positions or trajectory on-line of each robotic joint. The experimental results show that this visual servo control robot has reliable control actions.
机译:在改装的Mitsubishi Movemaster RV-M2机器人系统上实现了具有SOPC结构的视觉伺服控制系统。硬件电路具有正交编码器解码,限位开关检测,脉宽调制(PWM)生成和CMOS图像信号捕获的功能。 Nios II微处理器中嵌入的软件具有使用UART与PC进行通信,机器人逆运动学计算,机器人运动控制方案,数字图像处理和Gobang游戏AI算法的功能。数字硬件电路是使用Verilog语言设计的,并且Nios II微处理器中的程序是用C语言编码的。采用Altera Statrix II EP2S60F672C5Es FPGA芯片作为开发板的主CPU。选择了356×292像素分辨率的CMOS彩色图像传感器来捕捉环境随时间变化的变化,从而实现基于机器人视觉的伺服控制。系统性能通过实验测试进行评估。规划了一个五子棋游戏,以揭示非自主环境中的视觉伺服机器人运动控制目标。在此,采用了无模型智能自组织模糊控制策略来设计机器人关节控制器。设计基于视觉的轨迹规划算法,以在线计算每个机器人关节的所需角度位置或轨迹。实验结果表明,该视觉伺服控制机器人具有可靠的控制作用。

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