气泡状path

创建带箭头路径
-(CGPathRef)createPathWithArrowDirection:(MessageViewArrowDirection)direction AndRelativeOrigin:(CGPoint)reletiveOrigin
{

CGMutablePathRef path = CGPathCreateMutable();
CGRect rect;
if (reletiveOrigin.x<20) {
reletiveOrigin.x=20;
}
if (reletiveOrigin.x>self.bounds.size.width-20) {
reletiveOrigin.x=self.bounds.size.width-20 ;
}
if (reletiveOrigin.y<20) {
reletiveOrigin.y=20;
}
if (reletiveOrigin.y>self.bounds.size.height-20) {
reletiveOrigin.y=self.bounds.size.height-20 ;
}


if (direction==MessageViewArrowDirectionUp) {
rect=CGRectInset(self.bounds, 1, 10);
}
else if(direction==MessageViewArrowDirectionDown)
{
rect=CGRectInset(self.bounds, 1, 1);
rect.size.height=rect.size.height- 2*9;
}else if(direction==MessageViewArrowDirectionLeft)
{
rect=CGRectInset(self.bounds, 10, 1);
}
else if(direction==MessageViewArrowDirectionRight)
{
rect=CGRectInset(self.bounds, 1, 1);
rect.size.width=rect.size.width- 2*9;
}

CGFloat minx = CGRectGetMinX(rect), midx = CGRectGetMidX(rect), maxx = CGRectGetMaxX(rect);
CGFloat miny = CGRectGetMinY(rect), midy = CGRectGetMidY(rect), maxy = CGRectGetMaxY(rect);

CGFloat radius=10.0;
if (direction==MessageViewArrowDirectionUp) {

CGPathMoveToPoint(path, NULL, minx, midy);
CGPathAddArcToPoint(path, NULL, minx, miny, reletiveOrigin.x, miny, radius);
CGPathAddLineToPoint(path, NULL, reletiveOrigin.x, miny);
CGPathAddLineToPoint(path, NULL, reletiveOrigin.x+ARROW_WIDTH/2.0, 0);
CGPathAddLineToPoint(path, NULL, reletiveOrigin.x+ARROW_WIDTH, miny);
CGPathAddArcToPoint(path, NULL, maxx, miny, maxx, midy, radius);
CGPathAddArcToPoint(path, NULL, maxx, maxy, midx, maxy, radius);
CGPathAddArcToPoint(path, NULL, minx, maxy, minx, midy, radius);
}
else if(direction==MessageViewArrowDirectionDown)
{
CGPathMoveToPoint(path, NULL, minx, midy);
CGPathAddArcToPoint(path, NULL, minx, miny, midx, miny, radius);
CGPathAddArcToPoint(path, NULL, maxx, miny, maxx, midy, radius);
CGPathAddArcToPoint(path, NULL, maxx, maxy, reletiveOrigin.x+ARROW_WIDTH, maxy, radius);
CGPathAddLineToPoint(path, NULL, reletiveOrigin.x+ARROW_WIDTH, maxy);
CGPathAddLineToPoint(path, NULL, reletiveOrigin.x+ARROW_WIDTH/2.0, self.bounds.size.height);
CGPathAddLineToPoint(path, NULL, reletiveOrigin.x, maxy);
CGPathAddArcToPoint(path, NULL, minx, maxy, minx, midy, radius);
}else if(direction==MessageViewArrowDirectionLeft)
{
CGPathMoveToPoint(path, NULL, midx, miny);
CGPathAddArcToPoint(path, NULL, maxx, miny, maxx, midy, radius);
CGPathAddArcToPoint(path, NULL, maxx, maxy, midx, maxy, radius);
CGPathAddArcToPoint(path, NULL, minx, maxy, minx, reletiveOrigin.y+ARROW_HEIGHT, radius);
CGPathAddLineToPoint(path, NULL, minx, reletiveOrigin.y+ARROW_HEIGHT);
CGPathAddLineToPoint(path, NULL, self.bounds.origin.x, reletiveOrigin.y + ARROW_HEIGHT/2.0);
CGPathAddLineToPoint(path, NULL, minx, reletiveOrigin.y );
CGPathAddArcToPoint(path, NULL, minx, miny, midx, miny, radius);

}
else if(direction==MessageViewArrowDirectionRight)
{
CGPathMoveToPoint(path, NULL, minx, midy);
CGPathAddArcToPoint(path, NULL, minx, miny, midx, miny, radius);
CGPathAddArcToPoint(path, NULL, maxx, miny, maxx, reletiveOrigin.y, radius);
CGPathAddLineToPoint(path, NULL, maxx, reletiveOrigin.y);
CGPathAddLineToPoint(path, NULL, maxx+ARROW_WIDTH, reletiveOrigin.y+ARROW_HEIGHT/2.0);
CGPathAddLineToPoint(path, NULL, maxx, reletiveOrigin.y +ARROW_HEIGHT);
CGPathAddArcToPoint(path, NULL, maxx, maxy, midx, maxy, radius);
CGPathAddArcToPoint(path, NULL, minx, maxy, minx, midy, radius);
}

CGPathCloseSubpath(path);
return path;
}


内容概要:本文档围绕六自由度机械臂的ANN人工神经网络设计展开,涵盖正向与逆向运动学求解、正向动力学控制,并采用拉格朗日-欧拉法推导逆向动力学方程,所有内容均通过Matlab代码实现。同时结合RRT路径规划与B样条优化技术,提升机械臂运动轨迹的合理性与平滑性。文中还涉及多种先进算法与仿真技术的应用,如态估计中的UKF、AUKF、EKF等滤波方法,以及PINN、INN、CNN-LSTM等神经网络模型在工程问题中的建模与求解,展示了Matlab在机器人控制、智能算法与系统仿真中的强大能力。; 适合人群:具备一定Ma六自由度机械臂ANN人工神经网络设计:正向逆向运动学求解、正向动力学控制、拉格朗日-欧拉法推导逆向动力学方程(Matlab代码实现)tlab编程基础,从事机器人控制、自动化、智能制造、人工智能等相关领域的科研人员及研究生;熟悉运动学、动力学建模或对神经网络在控制系统中应用感兴趣的工程技术人员。; 使用场景及目标:①实现六自由度机械臂的精确运动学与动力学建模;②利用人工神经网络解决传统解析方法难以处理的非线性控制问题;③结合路径规划与轨迹优化提升机械臂作业效率;④掌握基于Matlab的态估计、数据融合与智能算法仿真方法; 阅读建议:建议结合提供的Matlab代码进行实践操作,重点理解运动学建模与神经网络控制的设计流程,关注算法实现细节与仿真结果分析,同时参考文中提及的多种优化与估计方法拓展研究思路。
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