comsol 采动影响下考虑塑性变形煤层瓦斯抽采模型comsol流固耦合瓦斯抽采模型
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comsol 采动影响下考虑塑性变形煤层瓦斯抽采模型comsol流固耦合瓦斯抽采模型 <link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/css/base.min.css" rel="stylesheet"/><link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/css/fancy.min.css" rel="stylesheet"/><link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/90214597/2/raw.css" rel="stylesheet"/><div id="sidebar" style="display: none"><div id="outline"></div></div><div class="pf w0 h0" data-page-no="1" id="pf1"><div class="pc pc1 w0 h0"><img alt="" class="bi x0 y0 w1 h1" src="/image.php?url=https://csdnimg.cn/release/download_crawler_static/90214597/bg1.jpg"/><div class="t m0 x1 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">一种基于人工势场法的复杂<span class="_ _0"> </span><span class="ff2">Frenet<span class="_ _1"> </span></span>弯道轨迹规划算法分析</div><div class="t m0 x1 h2 y2 ff1 fs0 fc0 sc0 ls0 ws0">一<span class="ff3">、</span>引言</div><div class="t m0 x1 h2 y3 ff1 fs0 fc0 sc0 ls0 ws0">在自动驾驶和智能移动机器人的路径规划中<span class="ff4">，</span>轨迹规划算法扮演着至关重要的角色<span class="ff3">。</span>针对复杂环境下</div><div class="t m0 x1 h2 y4 ff1 fs0 fc0 sc0 ls0 ws0">的轨迹规划问题<span class="ff4">，</span>本文提出了一种考虑人工势场法的复杂<span class="_ _0"> </span><span class="ff2">Frenet<span class="_ _1"> </span></span>弯道轨迹规划算法<span class="ff3">。</span>该算法通过引</div><div class="t m0 x1 h2 y5 ff1 fs0 fc0 sc0 ls0 ws0">入人工势场的概念<span class="ff4">，</span>结合<span class="_ _0"> </span><span class="ff2">Frenet<span class="_ _1"> </span></span>坐标系<span class="ff4">，</span>实现对移动物体的精确轨迹规划<span class="ff3">。</span></div><div class="t m0 x1 h2 y6 ff1 fs0 fc0 sc0 ls0 ws0">二<span class="ff3">、</span>人工势场法概述</div><div class="t m0 x1 h2 y7 ff1 fs0 fc0 sc0 ls0 ws0">人工势场法是一种虚拟力场方法<span class="ff4">，</span>通过在移动物体周围建立势场<span class="ff4">，</span>模拟物体在势场中的运动行为<span class="ff3">。</span>在</div><div class="t m0 x1 h2 y8 ff1 fs0 fc0 sc0 ls0 ws0">轨迹规划中<span class="ff4">，</span>人工势场法可以有效地处理复杂环境中的障碍物和道路约束<span class="ff4">，</span>为移动物体规划出平滑且</div><div class="t m0 x1 h2 y9 ff1 fs0 fc0 sc0 ls0 ws0">安全的轨迹<span class="ff3">。</span></div><div class="t m0 x1 h2 ya ff1 fs0 fc0 sc0 ls0 ws0">三<span class="ff3">、</span>基于人工势场法的<span class="_ _0"> </span><span class="ff2">Frenet<span class="_ _1"> </span></span>弯道轨迹规划算法</div><div class="t m0 x1 h2 yb ff2 fs0 fc0 sc0 ls0 ws0">1.<span class="_ _2"> </span>MATLAB<span class="_ _1"> </span><span class="ff1">实现</span></div><div class="t m0 x1 h2 yc ff1 fs0 fc0 sc0 ls0 ws0">在本算法中<span class="ff4">，</span>我们采用<span class="_ _0"> </span><span class="ff2">MATLAB<span class="_ _1"> </span></span>作为实现工具<span class="ff3">。<span class="ff2">MATLAB<span class="_ _1"> </span></span></span>具有强大的数值计算和可视化功能<span class="ff4">，</span>能够方</div><div class="t m0 x1 h2 yd ff1 fs0 fc0 sc0 ls0 ws0">便地实现轨迹规划算法<span class="ff3">。</span></div><div class="t m0 x1 h2 ye ff2 fs0 fc0 sc0 ls0 ws0">2.<span class="_ _2"> </span><span class="ff1">三圆碰撞检测原理</span></div><div class="t m0 x1 h2 yf ff1 fs0 fc0 sc0 ls0 ws0">为了处理移动物体与障碍物之间的碰撞问题<span class="ff4">，</span>我们采用三圆碰撞检测原理<span class="ff3">。</span>该原理通过比较物体<span class="ff3">、</span>障</div><div class="t m0 x1 h2 y10 ff1 fs0 fc0 sc0 ls0 ws0">碍物以及它们之间的相对位置关系<span class="ff4">，</span>判断是否存在碰撞风险<span class="ff3">。</span>其原理示意图如下<span class="ff4">（</span>此处可插入三圆碰</div><div class="t m0 x1 h2 y11 ff1 fs0 fc0 sc0 ls0 ws0">撞检测示意图<span class="ff4">）<span class="ff3">。</span></span></div><div class="t m0 x1 h2 y12 ff2 fs0 fc0 sc0 ls0 ws0">3.<span class="_ _2"> </span><span class="ff1">障碍物与道路人工势场的建立</span></div><div class="t m0 x1 h2 y13 ff1 fs0 fc0 sc0 ls0 ws0">在轨迹规划中<span class="ff4">，</span>我们需要根据障碍物的位置和形状<span class="ff4">，</span>以及道路的形状和约束<span class="ff4">，</span>建立相应的人工势场<span class="ff3">。</span></div><div class="t m0 x1 h2 y14 ff1 fs0 fc0 sc0 ls0 ws0">障碍物和道路上的势场会对移动物体产生力的作用<span class="ff4">，</span>引导物体避开障碍物并沿着道路行驶<span class="ff3">。</span></div><div class="t m0 x1 h2 y15 ff2 fs0 fc0 sc0 ls0 ws0">4.<span class="_ _2"> </span><span class="ff1">轨迹采样生成与最优求解</span></div><div class="t m0 x1 h2 y16 ff1 fs0 fc0 sc0 ls0 ws0">在本算法中<span class="ff4">，</span>我们通过采样法生成多个可能的轨迹<span class="ff4">，</span>然后利用优化算法对采样轨迹进行最优求解<span class="ff3">。</span>采</div><div class="t m0 x1 h2 y17 ff1 fs0 fc0 sc0 ls0 ws0">样过程中<span class="ff4">，</span>我们考虑势场的影响<span class="ff4">，</span>生成能够避开障碍物的安全轨迹<span class="ff3">。</span>最优求解则通过比较不同轨迹的</div><div class="t m0 x1 h2 y18 ff1 fs0 fc0 sc0 ls0 ws0">代价函数值<span class="ff4">，</span>选择最优的轨迹作为规划结果<span class="ff3">。</span></div><div class="t m0 x1 h2 y19 ff1 fs0 fc0 sc0 ls0 ws0">四<span class="ff3">、</span>算法优势分析</div></div><div class="pi" data-data='{"ctm":[1.568627,0.000000,0.000000,1.568627,0.000000,0.000000]}'></div></div>