四足机器人对角小跑动态控制

基于虚拟模型控制方法,根据四足机器人单腿雅克比矩阵得到支撑相与摆动相的控制法则。为实现机器人躯体的完全控制,提出了一种控制目标分解的方法,将四足机器人躯体的控制目标分解到每条支撑腿的控制上。通过构建每条支撑腿的虚拟构件,并将虚拟构件产生的虚拟力转换为期望关节力矩,从而实现支撑腿的虚拟模型控制;实时规划摆动足的运动轨迹,利用虚拟构件连接摆动腿的足端与期望的摆动轨迹,实现摆动腿的虚拟模型控制。在设定四条腿的相位轮换规律的基础上,对一个四足机器人二维平面模型进行对角小跑步态下的速度控制及抗干扰仿真试验。仿真结果证明该控制方法能够有效控制机器人躯体的高度、速度及倾角,实现四足机器人对角小跑运动的动态控制并具有一定的抗冲击干扰能力。     

基于SOPC和FPGA的智能机器人无线通讯系统设计

针对单处理器系统控制的机器人,其无线通信系统存在丢包现象和实时性差等弊端,设计了一种以FPGA作为机器人的主控制器,以PT2262/2272为通信芯片的无线通讯系统。该设计包括无线发射模块、接收模块、SOPC建立及软件实现。研究结果表明,该方案实现灵活,具有体积小、稳定性高、实时性好等优点,不仅解决了丢包的问题,而且具有一定的可扩展性。     

基于人工神经网络的操作手IKP 求解

人工神经网络以其信息的并行处理与分布式存储、自组织和自适应等特点,在机器人领域显示了极大的应用潜力。本文探讨人工神经网络在机器人操作手ＩＫＰ求解中的应用,试图求得操作手ＩＫＰ的一组或所有可行解。文章利用ＢＰ网络对操作手ＩＫＰ的求解进行了讨论和分析,并给出了具体的求解实例。     

机枪机器人的扫射方式和扫射角速度的研究

机枪机器人将在无人化战争中起到一定作用。使用者可以遥控射击,利用监视屏瞄准目标。由于图像传输延迟,监视屏上显示的图像反映目标在100 ms~300 ms之前的实际位置。射击移动目标是,如不考虑这一因素,将导致命中率降低。推导机枪机器人的扫射角速度计算式,对各种扫射方式进行分析和对比,以美制M240机枪为例进行仿真,进而找到了机枪机器人在平坦开阔地带的最优扫射方式。本方法可作为使用和设计机枪机器人的依据。     

基于虚拟模型控制的四足机器人对角小跑动态控制*

基于虚拟模型控制方法,根据四足机器人单腿雅克比矩阵得到支撑相与摆动相的控制法则。为实现机器人躯体的完全控制,提出了一种控制目标分解的方法,将四足机器人躯体的控制目标分解到每条支撑腿的控制上。通过构建每条支撑腿的虚拟构件,并将虚拟构件产生的虚拟力转换为期望关节力矩,从而实现支撑腿的虚拟模型控制;实时规划摆动足的运动轨迹,利用虚拟构件连接摆动腿的足端与期望的摆动轨迹,实现摆动腿的虚拟模型控制。在设定四条腿的相位轮换规律的基础上,对一个四足机器人二维平面模型进行对角小跑步态下的速度控制及抗干扰仿真试验。仿真结果证明该控制方法能够有效控制机器人躯体的高度、速度及倾角,实现四足机器人对角小跑运动的动态控制并具有一定的抗冲击干扰能力。     

弹药装填机器人作业平台仿真系统设计与实现

针对弹药装填机器人作业过程复杂的问题,基于作业任务实用性和可操作性的要求,设计了一种作业平台仿真系统。在深入分析弹药装填机器人作业任务和工作过程的基础上,构建了总体设计方案,研究了仿真系统的稳定性技术,进行了运动控制、数据采集以及传感器精度等硬件部分设计和模块化技术的软件设计,建立了弹药装填机器人仿真系统。仿真结果表明：该设计能够实现对弹药装填机器人的控制和实时作业。     

基于激光雷达的移动机器人实时位姿估计算法

提出一种基于二维激光雷达的移动机器人实时位姿估计算法。该算法首先将环境数据聚类为不同的障碍物,然后利用障碍物的特征匹配来关联相邻2帧的障碍物,最后通过优化位置序列间的方向角实现机器人的位姿估计。与ICP（迭代最近点）算法对比验证表明：该算法与ICP具有相同数量级的位姿估计精度,且明显提高了计算效率。     

一个监控式局部自主机器人控制器的实现与分析

本文介绍了一个严格监督控制（Ｓｕｐｅｒｖｉｓｏｒｙｃｏｎｔｒｏｌ）定义下的局部自主机器人控制器ＧＫＤ３的设计和实现，并从监督控制理论的角度，对ＧＫＤ３的体系结构和功能进行了分析和讨论。     

Adaptive fault-tolerant control based on boundary estimation for space robot under joint actuator faults and uncertain parameters

Since the joint actuator of the space robot executes the control instructions frequently in the harsh space environment, it is prone to the partial loss of control effectiveness (PLCE) fault. An adaptive fault-tolerant control algorithm is designed for a space robot system with the uncertain parameters and the PLCE actuator faults. The mathematical model of the system is established based on the Lagrange method, and the PLCE actuator fault is described as an effectiveness factor. The lower bound of the effectiveness factors and the upper bound of the uncertain parameters are estimated by an adaptive strategy, and the estimated value is fed back to the control algorithm. Compared with the traditional fault-tolerant algorithms, the proposed algorithm does not need to predetermine the lower bound of the effectiveness factor, hence it is more in line with the actual engineering application. It is proved that the algorithm can guarantee the stability of the closed-loop system based on the Lyapunov function method. The numerical simulation results show that the proposed algorithm can not only compensate for the uncertain parameters, but also can tolerate the PLCE actuator faults effectively, which verifies the effectiveness and superiority of the control scheme.     

Knowledge-oriented modeling for influencing factors of battle damage in military industrial logistics: An integrated method

Modeling influencing factors of battle damage is one of essential works in implementing military industrial logistics simulation to explore battle damage laws knowledge. However, one of key challenges in designing the simulation system could be how to reasonably determine simulation model input and build a bridge to link battle damage model and battle damage laws knowledge. In this paper, we propose a novel knowledge-oriented modeling method for influencing factors of battle damage in military industrial logistics, integrating conceptual analysis, conceptual modeling, quantitative modeling and simulation implementation. We conceptualize influencing factors of battle damage by using the principle of hierarchical decomposition, thus classifying the related battle damage knowledge logically. Then, we construct the conceptual model of influencing factors of battle damage by using Entity-Relationship approach, thus describing their interactions reasonably. Subsequently, we extract the important influencing factors by using social network analysis, thus evaluating their importance quantitatively and further clarifying the elements of simulation. Finally, we develop an agent-based military industry logistics simulation system by taking the modeling results on influencing factors of battle damage as simulation model input, and obtain simulation model output, i.e., new battle damage laws knowledge, thus verifying feasibility and effectiveness of the proposed method. The results show that this method can be used to support human decision-making and action.