食品协作机器人动态目标抓取控制方法研究

目的:解决目前协作机器人在食品动态目标抓取中存在的准确性较低问题。方法:基于协作机器人体系结构,提出将模糊自整定PID控制和鲁棒自适应补偿器相结合用于协作机器人食品动态目标抓取。PID结合模糊控制完成参数自整定,鲁棒算法与自适应算法相结合用于系统不确定性补偿。通过试验分析了所提方法的性能,验证了该方法的可行性。结果:所提方法在协作机器人动态目标抓取中具有较好的效果,提高了协作机器人动态抓取的准确性,在传送带速度100 mm/s时,动态抓取成功率达到99.50%,对食品动态目标抓取具有一定的应用价值。结论:通过优化现有目标抓取控制方法,可有效提高协作机器人的抓持精度。     

足式步行机器人的动态仿真及结构优化

利用UG对足式步行机器人进行实体建模,基于动态仿真软件ADAMS对其运动进行了动态仿真,得到其运动的关联性。结合正交试验法对足式步行机器人的驱动机构进行了优化,分析了其差动量的变化关系,得到了机构的最优解,为实际工程提供了可靠依据。     

一种基于粒子群参数优化的改进蚁群算法及其应用

针对现有基于粒子群参数优化的改进蚁群算法耗时较大的问题,提出了一种新的解决方案.方案中采用一种全局异步与精英策略相结合的信息素更新方式,同时合理减少蚁群算法被粒子群算法调用一次所需的迭代代数.对日本旭川垃圾场巡查机器人路径规划问题仿真求解的结果表明,与其他算法相比,该改进算法具有比较明显的速度优势.     

吸尘机器人的现状及其智能系统的若干关键技术

吸尘机器人能实现室内环境全自动清洁,替代了传统的人工清洁,具有十分广阔的市场前景。介绍了国内外吸尘机器人产品现状;综合评述了其智能系统中的全区域覆盖、路径规划、环境建模及传感器等的研究现状,对关键技术的难点进行了说明,并对其发展前景做了展望。     

Point stabilization of mobile robots via state-space exact feedback linearization

In this paper, we solve the point stabilization of mobile robots via state-space exact feedback linearization. The state-space exact feedback linearization has not been possible in the past for the point stabilization of mobile robots due to the restricted mobility caused by nonholonomic constraints. Under some proposed coordinates, however, the point stabilization problem can be exactly transformed into the problem of controlling a linear time-invariant system. Thus, using well-established linear control theory, the point stabilization of robots can be easily formulated.     

机器人行走运动软件设计

在前期对游乐园所要求的机器人服务系统开发基础上,设计了机器人的行走运动程序、机器人行走中避开碰撞物体程序和视觉驱动设计。这些程序可以分别使机器人在行走的时候更加自如、使机器人就可以感知和避免来自前方的碰撞,以及使机器人能够识别和根据外界光线的强弱来决定行走路线。本设计有效地提高了机器人的运动功能。     

中值流辅助在线多示例目标跟踪

针对机器人演示学习中目标跟踪性能的严格要求,提出一种可以有效克服快速运动、遮挡和目标漂移的物体跟踪方法.首先计算中值流,并预测目标的位置偏移,以此计算高斯权重;然后修正搜索区域,并使用在线多示例分类器进行目标搜索,计算似然度;最后使用贝叶斯框架对结果进行融合,使用穷举搜索得到最优的预测位置,并更新在线分类器.实验结果表明,与现有方法相比,该方法对快速运动和目标漂移具有更强的鲁棒性,而且可以达到实时跟踪.     

改进的混合蛙跳移动机器人路径规划算法

为了实现移动机器人在障碍环境中的路径规划,提出一种改进的混合蛙跳算法(SFLA).改进算法在原算法基础上引入交叉操作,并在青蛙更新策略中充分利用学习机制;此外提出了一种带控制参数的产生新个体的方法代替原本的随机更新操作.把路径规划问题转换为最小化问题,基于环境中目标和障碍物的位置定义青蛙的适应度,机器人依次到达每次迭代中最好蛙的位置,从而实现最优路径规划.移动机器人仿真实验中,与基本蛙跳算法和其他智能算法相比,改进算法在规划时间和成功次数上均有很大的提高.实验结果表明了改进算法的有效性.     

Towards load-balanced de-congested multi-robotic agent traffic control by coordinated control at intersections

This paper presents a methodology for the coordination of multiple robotic agents moving from one location to another in an environment embedded with a network of agents, placed at strategic locations such as intersections. These intersection agents, communicate with robotic agents and also with each other to route robots in a way as to minimize the congestion, thus resulting in the continuous flow of robot traffic. A robot’s path to its destination is computed by the network (in this paper, ‘Network’ refers to the collection of ‘Network agents’ operating at the intersections) in terms of the next waypoints to reach. The intersection agents are capable of identifying robots in their proximity based on signal strength. An intersection agent controls the flow of agent traffic around it with the help of the data it collects from the messages received from the robots and other surrounding intersection agents. The congestion of traffic is reduced using a two-layered hierarchical strategy. The primary layer operates at the intersection to reduce the time delay of robots crossing them. The secondary layer maintains coordination between intersection agents and routes traffic such that delay is reduced through effective load balancing. The objective at the primary level, to reduce congestion at the intersection, is achieved through assigning priorities to pathways leading to the intersection based on the robot traffic density. At the secondary level, the load balancing of robots over multiple intersections is achieved through coordination between intersection agents by communication of robot densities in different pathways. Extensive comparisons show the performance gain of the current method over existing ones. Theoretical analysis apart from simulation show the advantages of load-balanced traffic flow over uncoordinated allotment of robotic agents to pathways. Transferring the burden of coordination to the network releases more computational power for the robots to engage in critical assistive activities.     

旋翼飞行机器人故障诊断与容错控制技术综述

对故障诊断和容错技术的发展过程进行了简要概述，以旋翼飞行机器人为研究对象，在分析了旋翼飞行机器人故障诊断与容错控制特点的基础上，介绍了当前国内外在该领域的研究进展和主要方法．最后，总结了该领域待解决的难点问题，并指出了该研究领域的发展趋势．