基于逆运动学降维求解与YOLO v4的果实采摘系统研究

为提高采摘设备的执行效率，采用六自由度机械臂、树莓派、Android手机端和服务器设计了一种智能果实采摘系统，该系统可自动识别不同种类的水果，并实现自动采摘，可通过手机端远程控制采摘设备的起始和停止，并远程查看实时采摘视频。提出通过降低自由度和使用二维坐标系来实现三维坐标系中机械臂逆运动学的求解过程，从而避免了大量的矩阵运算，使机械臂逆运动学求解过程更加简捷。利用Matlab中的Robotic Toolbox进行机械臂三维建模仿真，验证了降维求解的可行性。在果实采摘流程中，为了使机械臂运动轨迹更加稳定与协调，采用五项式插值法对机械臂进行运动轨迹规划控制。基于Darknet深度学习框架的YOLO v4目标检测识别算法进行果实目标检测和像素定位，在Ubuntu 19.10操作系统中使用2000幅图像作为训练集，分别对不同种类的果实进行识别模型训练，在GPU环境下进行测试，结果表明，每种果实识别的准确率均在94%以上，单次果实采摘的时间约为17s。经过实际测试，该系统具有良好的稳定性、实时性以及对果实采摘的准确性。     

一类6自由度Delta型机器人运动学分析

为满足工业机器人多角度操作需求,提出了一类具有3组耦合分支,且对称分布的6自由度Delta型机器人。首先,将每组耦合分支拆分为独立运动单元,并等效为串联运动链,基于旋量理论求出等效后的运动自由度;其次,利用闭环矢量回路法分别计算耦合分支中每条主动链的位置逆解,建立机器人的逆运动学模型;在此基础上,提出一种搜索算法,用于描绘满足边界条件的机器人运动空间,并与相同尺度参数的3自由度Delta机器人进行对比。结果表明,3自由度Delta机器人的运动空间是所提机器人工作空间的子集。最后,根据理论分析,完成了工程样机的搭建与运动实验,实验结果表明,该Deta型机器人具有6个自由度运动能力,且所提运动空间搜索算法具有较高的计算精度。     

Analysis of sinking death using video images of the swimming performance of Pacific Bluefin tuna (Thunnus orientalis) larvae

In this study, we aimed to clarify the mechanism of sinking death during the larval stage of Pacific Bluefin tuna Thunnus orientalis by investigating the effects of swimming performance on sinking death, using a behavioral approach. Swimming performance was examined 3–9 days after hatching (DAH) under day and night light conditions in cuboid experimental tanks. Swimming behavior variables such as swimming speed and swimming angle were measured under both light conditions. Larvae in the daytime experiment and larvae with inflated swim bladders at night were distributed on the surface layer of the water column. In contrast, larvae with uninflated swim bladders at night were frequently observed swimming vertically or sinking to the bottom of the tank. Larvae with inflated swim bladders at night were always distributed beneath the surface until the next morning (survival rates were 100 %). However, larvae with uninflated swim bladders at night swam upward repeatedly and later sank to the bottom of the tank (survival rates were 60 % and 38 % at 5 and 9 DAH, respectively). Larvae with uninflated swim bladders were not always able to maintain their swimming depth by swimming until the next morning. Additionally, their swimming speed and vertical swimming frequency (ratio) depended on the illumination and swim bladder conditions. Our findings show that larvae with uninflated swim bladders at night were associated with a higher risk of sinking death. The swimming energy capacity of Pacific Bluefin tuna larvae, which indicates the total amount of the energy that enables individuals to swim throughout the night without feeding, was found to be linked to sinking death.     

Assessing appetite of the swimming fish based on spontaneous collective behaviors in a recirculating aquaculture system

In order to realize the real-time appetite-based feeding in aquaculture, a novel and practical method, based on the quantification of the spontaneous collective behaviors, was proposed in this study to assess the real-time appetite of the swimming fish in a recirculating aquaculture system. First, foreground feature points of fish school were extracted using an improved complex network. Then, covariance, a modified social force model and a kinetic energy model were used to analyze the collective behaviors of the school from perspectives of dispersion degree, interaction force and the changing magnitude of the water flow field, respectively. Finally, the quantified behavioral characteristics were integrated and used to assess the appetite of fish school. The presented method shows its good performance in the expression of the collective behaviors representing five typical appetites (0.01, 0.52, 1.28, 2.26 and 2.92), and the assessing accuracy of the appetite of the school is also maintained at a low non-match rate ((2.19 ± 0.81)% best) in the context of ten different sampling durations.     

关于点的合成运动中的两个问题

本文讨论了在合成运动中，动点与动参考系的选取，相对运动轨迹对计算点的绝对速度和绝对加速度的影响．证明了相对运动轨迹只对点的绝对加速度计算有影响，阐明了选取动点和动参考系的原则．     

高校游泳运动研究概述

游泳运动具有良好的身心锻炼价值,将其列为高校体育课程会收到良好的育人效果.纵观国内外发达地区和先进高校开展游泳课程的历程,可以知道,我国高校开设游泳课程拥有很大的空间和潜力     

基于改进蚁群算法的3-PPR并联机构位置正解研究

针对3-PPR并联机构位置正解问题,运用螺旋理论计算其自由度,并分析其运动特性,同时通过解析法构建该并联机构的完整运动学逆解。将并联机构运动学正解问题的求解转化为对目标函数优化问题的求解,并基于此建立该并联机构正解的目标函数优化模型。通过对基本蚁群算法进行有效的改进,构建了可用于求解连续优化问题的改进蚁群算法。运用该算法求解3-PPR并联机构的运动学正解并进行Matlab仿真分析,对比传统数值方法和改进蚁群算法,证实该算法具有良好的全局寻优能力,并能避免初值和局部最优值对计算结果的影响,可有效应用于求解并联机构的位置正解问题。     

油葵收获割台工作性能仿真及试验研究

为研究油葵收获割台在工作过程中的性能与可靠性,得到该割台正常工作时的关键参数,利用SOLIDWORKS对割台进行三维参数化建模并导入ADAMS中进行运动学仿真,得到收获时茎秆受力和摆动程度的仿真结果并进行正交组合分析,仿真和分析结果表明:割台正常工作最优参数的组合是拉茎辊转速800 r/min、机器的行驶速度2.12 km/h、拉茎间隙10 mm、拉茎辊的倾角20°,同时往复切割刀的切割速度2 m/s时茎秆的受力最小,通过田间试验发现整个收获过程籽粒损失率≤3%,喂入输送绞龙的茎秆较短,收获可靠性较好,结果表明该割台适合油葵的机械化收获。     

COMAU-120机器人逆运动学分析及其求解

机器人逆运动学在机器人学中占有非常重要的地位。为此,建立了COMAU-120机器人的运动学模型,并利用奇次变换导出了逆运动学求解公式。机器人逆运动学分析方法在实际中得到了应用,为实现弧焊机器人系统路径规划和离线编程奠定了基础。     

一般6R机器人的高精度逆运动学优化算法

为提高一般6R机器人逆运动学算法的精度和效率,提出一种基于符号运算和矩阵分解的优化算法。对6个基础逆运动学方程作变换,采用符号运算预处理得到14个逆运动学方程,避免大量浮点数计算累积误差。利用其中6个方程与关节变量3无关的特点,将目标矩阵从24阶降低到16阶,包含的关节变量从3个增加到4个。把一元16次方程求根问题转换为矩阵特征分解问题,并选取较高数量级的相关数据元素计算关节变量,进一步提高了算法精度。以一般6R机器人为例,求解结果表明,提出的算法能够得到具有任意期望精度的最多16组实数逆运动学解。