基于Arduino的四自由度机械臂控制

随着控制技术的不断改进,机械臂的应用越来越广泛。文章设计了一种基于Arduino的四自由度机械臂,使用Arduino作为系统主控模块,结合舵机驱动模块、按键模块和金属机械臂搭建硬件系统,并使用专门的IDE软件完成软件设计。最终可以通过8个按键对金属机械臂进行快捷控制,从而实现机械臂对物体进行抓取的功能。     

智能机械臂的压电半主动振动控制

以在半主动控制领域具有良好应用前景的压电元件为基础,在受控机械臂上粘贴压电陶瓷(PZT)片,运用基于压电分流阻尼的振动被动控制和基于同步开关阻尼(SSD)技术的半主动控制理论,消耗机械臂振动的机械能,减小结构振动的位移幅度,从而达到振动控制的目的.     

基于Arduino单片机模拟搜救其系统的设计与实现

设计一款基于Arduino单片机的机械臂,通过Arduino单片机实现对机械臂舵机系统的运动控制,使其完成不同位置的抓取动作。本文首先从实际角度分析机械臂技术在直升机搜救中的应用,随后基于实际情况探究模拟机械臂的控制方案,之后介绍了基于Arduino单片机六自由度机械臂的硬件结构和系统软件设计。在实际应用情况下,则是将其吊装在直升机模型下,用于参加全国航空航天模型锦标赛中的模拟直升机空中搜救。     

融合视觉的机械臂抓取策略综述

根据目前机械臂的发展状况,针对融合视觉的机械臂机械抓取策略做简要综述,基于视觉的机械臂抓取策略主要分为三个发展历程:基于单双目结合视觉、基于Kinect二维深度视觉,基于Ensenso N10三维深度视觉的机械臂抓取。简述各个阶段的发展状况,以及各自的优越性和局限性,并展望了融合视觉的机械臂抓取策略的下一步发展方向。     

基于Ｔａｙｌｏｒ Ｓｅｒｉｅｓ－ＬＱＲ复合策略的双关节机械臂时滞补偿控制

为解决时滞导致的颤振问题,提出了一种基于Taylor Series-LQR复合策略的双关节机械臂时滞补偿控制方法。首先,利用两个一阶泰勒级数分别构建基于两机械臂当前理想控制力预测下一时滞时刻的理想控制力的预测方程;然后,利用此二预测方程对描述双关节机械臂运动的状态方程进行扩展;最后,根据LQR控制策略设计时滞补偿预测控制器求取预测控制力。应用结果显示,随着时滞的变大,使用无补偿措施的LQR(Linear Quadratic Regulator)控制器的双关节机械臂的颤振逐渐增大,并最终走向运动发散,而使用Taylor Series-LQR时滞补偿预测控制器的双关节机械臂在较大时滞范围内均能稳定跟踪期望轨迹而不产生颤振,说明Taylor Series-LQR复合策略具有良好的双关节机械臂时滞补偿效果。     

基于安卓的多功能机械臂研究与设计

为了降低机械臂的使用门槛,提高机械臂的通用性;设计并制作了一套基于安卓和电脑客户端的多功能机械臂;其系统的关键是上位机软件的开发,Wi-Fi通信技术,单片机系统电路的设计,机械臂及无线摄像头的配置和编程;经过实地测验,多次调整控制精度,圆满地实现了预期功能。     

基于机械臂路径规划的内场轨迹实现技术研究

为了解决传统光电跟踪设备的跟踪性能测试系统参数调试繁琐、设备安装困难、靶标适用性差等问题,研究了基于机械臂路径规划的内场轨迹实现技术。通过规划六自由度机械臂的末端运动轨迹,设计了更加灵活、高效的跟踪性能测试系统。首先,对传统测试靶标系统进行分析,明确实现跟踪性能测试的数学模型;然后提出基于六自由度机械臂的新型技术方案,并分析了两种方案的差异性;接着通过靶标轨迹的坐标变换,根据传统动态靶标轨迹得到适用于六自由度机械臂的末端位姿参数,从而实现轨迹规划;最后,通过数值仿真验证了本文方法与传统方法的跟踪性能测试效果的一致性。仿真结果表明,两者具有相同的跟踪性能测试效果。相较于传统方法,采用机械臂的测试系统在参数调节、工具安装和靶标适用性上更具优势,完全能够满足光电跟踪设备内场跟踪性能测试的要求。     

基于虚拟现实交互的机械臂协同控制

虚拟现实(Virtual Reality)是一种利用计算机硬件和软件集成的技术,对计算机图形学、人机交互、多媒体、网络通信等多种技术进行综合应用,从而为用户提供虚拟三维世界体验的一种技术。传统机械臂远程控制普遍采用的是手柄和键盘控制方式,而且今后方式普遍是摄像头图像显示在监控器上,和现场操作差别很大。协同控制机械臂将人的主观能动性与机械臂精确作业结合起来,可以实现在人类不能到达的特定环境下,利用远端机器人进行作业,同时通过VR系统模拟真实环境为用户提供身临其境的体验。本文主要以Unity3d引擎为支撑,头戴式显示设备HTC VIVE作为虚拟现实硬件设备,通过Steam VR设计与实现一个具备通用交互行为功能的VR交互场景,利用Socket通信将VR系统与机械臂进行连接,从而实现与机械臂的交互协同控制。     

采摘机器人机械臂的控制与联合仿真

采摘机器人属于非结构环境下作业的特种机器人,果实的采摘易受环境变化的影响,机械臂的控制直接决定采摘机器人的作业效果.根据番茄的特点及其植株的生长分布,设计了具有平行结构关节的四自由度机械臂,实现了对机械臂各个关节的控制.使用ADAMS/Controls与MATLAB/simulink进行联合仿真,根据仿真结果,不断调节控制参数,实现了机械臂的运动规划和性能指标的优化.     

基于DSP仿人机器人关节控制器设计

在具有32自由度仿人机器人中,为了每一个关节动作准确,可以采用分布式控制的体系结构.这里采用基于RS 485总线的TMS320F240DSP作为分布式关节控制器.非常适合于在机械臂内的狭小空间内安装,并进行增量码盘和速度检测电路的设计以及相应的软件设计等,完成了6个自由度机械臂分布式关节控制器设计,能够满足仿人机器人技术与系统的运动轨迹的要求.     

Learning cooperative dynamic manipulation skills from human demonstration videos

This article proposes a method for learning and robotic replication of dynamic collaborative tasks from offline videos. The objective is to extend the concept of learning from demonstration (LfD) to dynamic scenarios, benefiting from widely available or easily producible offline videos. To achieve this goal, we decode important dynamic information, such as the Configuration Dependent Stiffness (CDS), which reveals the contribution of arm pose to the arm endpoint stiffness, from a three-dimensional human skeleton model. Next, through encoding of the CDS via Gaussian Mixture Model (GMM) and decoding via Gaussian Mixture Regression (GMR), the robot’s Cartesian impedance profile is estimated and replicated. We demonstrate the proposed method in a collaborative sawing task with leader–follower structure, considering environmental constraints and dynamic uncertainties. The experimental setup includes two Panda robots, which replicate the leader–follower roles and the impedance profiles extracted from a two-persons sawing video.     

Intelligent assistance for older adults via an admittance-controlled wheeled mobile manipulator with task-dependent end-effectors

The increase in the ageing population worldwide poses a severe challenge in assisting older individuals to live independently, including the provision of mobility assistance and support in daily activities. In this paper, a practical robotic system is developed to provide intelligent support for older persons using a wheeled mobile manipulator (WMM), consisting of an omnidirectional mobile platform and a robotic arm. We focus on two critical needs: (1) mobility assistance, and (2) object manipulation support. The tasks are not executed simultaneously and each uses a task-dependent end-effector. Learning from demonstration, or kinesthetic teaching, is adopted to help the WMM to learn an elderly or disabled user’s walking pattern or an able-bodied person’s object manipulation skill. The robotic system can assist the user in conducting a number of daily operations. For mobility assistance, the WMM is reconfigured into a smart walker, where a novel variable admittance control is adopted to detect the user’s walking intention. A learning approach based on dynamic movement primitives is implemented to capture and adapt the WMM to the user’s walking pattern. For object manipulation support, a demonstrator first collaborates with an elderly user to conduct the task, and then the WMM takes the role of the demonstrator to assist the user. The Gaussian mixture model and Gaussian mixture regression are used to learn and reproduce the demonstrator’s experience, respectively. The advantages and effectiveness of the proposed approach are experimentally demonstrated with a four-wheel omnidirectional WMM.     

一种基于深度增强学习的智能路由技术

随着网络规模的不断增大以及网络复杂度的不断提高,传统路由算法面对网络流量在时空分布上的剧烈波动难以兼顾计算复杂度和算法效率.近年来,随着软件定义网络和人工智能技术的兴起,基于机器学习的自动路由策略生成逐渐受到关注.本文提出一种基于深度增强学习的智能路由技术SmartPath,通过动态收集网络状态,使用深度增强学习自动生成路由策略,从而保证路由策略能够动态适应网络流量变化.实验结果表明,本文所提出的方案能够不依赖人工流量建模动态更新网络路由,在测试环境下比当前最优方案减少至少10%的平均端到端传输时延.     

Assessment of average muscle fiber conduction velocity from surface EMG signals during fatiguing dynamic contractions

In this paper, we propose techniques of surface electromyographic (EMG) signal detection and processing for the assessment of muscle fiber conduction velocity (CV) during dynamic contractions involving fast movements. The main objectives of the study are: 1) to present multielectrode EMG detection systems specifically designed for dynamic conditions (in particular, for CV estimation); 2) to propose a novel multichannel CV estimation method for application to short EMG signal bursts; and 3) to validate on experimental signals different choices of the processing parameters. Linear adhesive arrays of electrodes are presented for multichannel surface EMG detection during movement. A new multichannel CV estimation algorithm is proposed. The algorithm provides maximum likelihood estimation of CV from a set of surface EMG signals with a window limiting the time interval in which the mean square error (mse) between aligned signals is minimized. The minimization of the windowed mse function is performed in the frequency domain, without limitation in time resolution and with an iterative computationally efficient procedure. The method proposed is applied to signals detected from the vastus laterialis and vastus medialis muscles during cycling at 60 cycles/min. Ten subjects were investigated during a 4-min cycling task. The method provided reliable assessment of muscle fatigue for these subjects during dynamic contractions.     

An enhanced MAC protocol based on the IEEE 802.11 for data relay satellite systems

Data relay satellite (DRS) systems play an important role in space information networks. Characterized by highly dynamic topology and discontinuous communication links, it is suggested that the IEEE 802.11 protocol employed in such a network could be more flexible. However, such a terrestrial network protocol could not be applied to DRS systems directly, nor supports a fast response due to the long propagation delay and severe packet collision. To address this challenge, we proposed an enhanced media access control (MAC) protocol based on the IEEE 802.11 protocol providing multiaccess for low earth orbit (LEO) distributed constellations. In this paper, we investigated the access delay performance of the proposed protocol in our model. Then, we derived a contention window adaption by using an iteration algorithm that can dynamically adjust the values of the contention window depending on the number of user satellites in the communication coverage. Simulation results show that the average access delay does not exceed 20 seconds, which is significantly lower than the standard protocol. Moreover, the traffic threshold is increased to 0.6, and the maximum throughput has doubled compared with the standard protocol. It is proved that the enhanced MAC protocol shows a better performance in DRS systems.     

Fair end‐to‐end window‐based congestion control in time‐varying data communication networks

Communication networks are time varying and, hence, fair sharing of network resources among the users in such a dynamic environment is a challenging task. In this context, a time‐varying network model is designed, and the shortest user's route is found. In the designed network model, an end‐to‐end window‐based congestion control scheme is developed with the help of internal nodes or router, and the end user can get implicit feedback (throughput). This scheme is considered as fair if the allocation of resources among users minimizes overall congestion or backlog in the networks. Window update approach is based on a multi‐class fluid model and is updated dynamically by considering delays (communication, propagation, and queuing) and the backlog of packets in the user's routes. Convergence and stability of the window size are obtained using a Lyapunov function. A comparative study with other window‐based methods is also provided.     

OFDM-UWB系统的自适应联合信道估计算法

提出了一种新的MB-OFDM-UWB自适应联合信道估计算法,该算法首先对基于DFT的信道估计算法进行改进,使其能自适应的调整滤波窗口的大小。然后利用改进后的算法与梳状导频估计相结合。算法的优点在于能根据不同的信道的统计特征,自适应调整滤波器窗口的大小,从而减少了噪声对信道估计的影响,并保留了梳状导频估计能快速跟踪信道变化的特性。仿真结果表明,该算法能很好地适用于UWB室内信道。     

Combining Task Scheduling in Power Adaptive Dynamic Reconfigurable System

Supplying the electronic equipment by exploiting ambient energy sources is a hot spot. In order to achieve the match between power supply and demands under the variance of environments at real time, a reconfigurable technique is taken. In this paper, a dynamic power consumption model by using a lookup table as a unit is proposed. Then, we establish a system-level task scheduling model according to the task type. Based on single instruction multiple data (SIMD) architecture which contains a processing system and a control system with a Nios Ⅱ processor, a practical dynamic reconfigurable system is built. The approach is evaluated on a hardware platform. The test results show that the system can automatically adjust the power consumption in case of external energy input changing. The utilization of the system dynamic power of their portion is from 80.05% to 91.75% during the first task assignment. During the entire processing cycle, the total energy efficiency is 97.67%.     

Optimal Dynamic Voltage Scaling in Energy-Limited Nonpreemptive Systems with Real-Time Constraints

Dynamic voltage scaling is used in energy-limited systems as a means of conserving energy and prolonging their life. We consider a setting in which the tasks performed by such a system are nonpreemptive and aperiodic. Our objective is to control the processing rate over different tasks so as to minimize energy subject to hard real-time processing constraints. Under any given task scheduling policy, we prove that the optimal solution to the offline version of the problem can be efficiently obtained by exploiting the structure of optimal sample paths, leading to a new dynamic voltage scaling algorithm termed the critical task decomposition algorithm (CTDA). The efficiency of the algorithm rests on the existence of a set of critical tasks that decompose the optimal sample path into decoupled segments within which optimal processing times are easily determined. The algorithm is readily extended to an online version of the problem as well. Its worst-case complexity of both offline and online problems is O(N²)     

动态时间窗下的相控阵雷达自适应调度算法

针对相控阵雷达任务调度问题,该文提出了一种基于动态时间窗的任务调度方法。该方法根据目标跟踪滤波中的残差和雷达对目标跟踪波门之间的约束关系以及搜索帧周期的约束,分别实现对跟踪任务和搜索任务的时间窗计算。最后将该方法与传统固定时间窗方法进行对比仿真,仿真结果证明了所提方法的有效性和优越性。