基于解析法的四轴SCARA机器人正逆运动学代码

一、正运动学实现(C++)

#include <cmath>
#include <array>

struct Pose {
    double x, y, z;  // 末端位姿
    double yaw;      // 末端偏航角
};

// DH参数定义(示例值)
const double L1 = 0.2;  // 基座到J2连杆长度
const double L2 = 0.3;  // J2到J3连杆长度
const double L3 = 0.15; // J3垂直移动行程

// 正运动学计算
Pose forwardKinematics(double theta1, double theta2, double d3, double theta4) {
    Pose pose;
    
    // 平面位置计算
    pose.x = L1 * cos(theta1) + L2 * cos(theta1 + theta2);
    pose.y = L1 * sin(theta1) + L2 * sin(theta1 + theta2);
    pose.z = d3;  // 垂直方向位移
    
    // 姿态计算
    double yaw = theta1 + theta2 + theta4;
    pose.yaw = yaw;
    
    return pose;
}

二、逆运动学实现(C++)

#include <array>
#include <cmath>

// 逆运动学求解(带奇异点检测)
bool inverseKinematics(const Pose& target, 
                      double& theta1, double& theta2, 
                      double& d3, double& theta4) {
    // 奇异点检测(工作空间边界)
    double r = std::sqrt(target.x * target.x + target.y * target.y);
    if(r > (L1 + L2) || r < std::abs(L1 - L2)) {
        return false;  // 超出工作空间
    }

    // 关节角度计算(几何法)
    double k1 = L1 + L2 * cos(target.yaw);
    double k2 = L2 * sin(target.yaw);
    
    // 计算θ2(两解)
    double cos_theta2 = (target.x*k1 + target.y*k2) / (r*(L1*L1 + L2*L2 + 2*L1*L2*cos(target.yaw)));
    double sin_theta2 = (target.y*k1 - target.x*k2) / (r*(L1*L1 + L2*L2 + 2*L1*L2*cos(target.yaw)));
    
    double theta2_1 = std::atan2(sin_theta2, cos_theta2);
    double theta2_2 = theta2_1 + M_PI;  // 第二解
    
    // 选择最近解(根据当前关节状态优化)
    double current_theta2 = 0.0;  // 假设当前角度为0
    double delta1 = std::abs(theta2_1 - current_theta2);
    double delta2 = std::abs(theta2_2 - current_theta2);
    
    double selected_theta2 = (delta1 < delta2) ? theta2_1 : theta2_2;

    // 计算θ1
    theta1 = std::atan2(target.y, target.x) 
           - std::atan2(L2 * sin(selected_theta2), L1 + L2 * cos(selected_theta2));
    
    // 计算d3
    d3 = target.z;

    // 计算θ4
    theta4 = target.yaw - theta1 - selected_theta2;

    return true;
}

三、工程优化策略

1. 关节限位处理

// 关节角度约束(示例范围)
const double theta_min[4] = {-M_PI/2, -M_PI/2, 0.0, -M_PI};
const double theta_max[4] = {M_PI/2, M_PI/2, 0.5*M_PI, M_PI};

// 角度约束函数
void clampAngles(double& angle, double min_val, double max_val) {
    while(angle > max_val) angle -= 2*M_PI;
    while(angle < min_val) angle += 2*M_PI;
    angle = std::max(min_val, std::min(max_val, angle));
}

2. 多解选择策略

// 多解生成与选择
std::array<double, 4> getMultipleSolutions(const Pose& target) {
    std::array<double, 4> solutions;
    
    // 生成θ2的两个解
    double k1 = L1 + L2 * cos(target.yaw);
    double k2 = L2 * sin(target.yaw);
    
    double cos_theta2 = (target.x*k1 + target.y*k2) / (r*(L1*L1 + L2*L2 + 2*L1*L2*cos(target.yaw)));
    double sin_theta2 = (target.y*k1 - target.x*k2) / (r*(L1*L1 + L2*L2 + 2*L1*L2*cos(target.yaw)));
    
    double theta2_1 = std::atan2(sin_theta2, cos_theta2);
    double theta2_2 = theta2_1 + M_PI;
    
    // 选择最优解(基于最小能量)
    double current_theta2 = 0.0;  // 假设当前角度
    double delta1 = std::abs(theta2_1 - current_theta2);
    double delta2 = std::abs(theta2_2 - current_theta2);
    
    solutions[1] = (delta1 < delta2) ? theta2_1 : theta2_2;
    solutions[3] = (delta1 < delta2) ? theta2_2 : theta2_1;  // 对称解
    
    return solutions;
}

四、完整控制流程

int main() {
    // 目标位姿(示例)
    Pose target = {0.5, 0.3, 0.2, M_PI/4};
    
    // 逆解计算
    double theta1, theta2, d3, theta4;
    if(!inverseKinematics(target, theta1, theta2, d3, theta4)) {
        std::cerr << "目标点超出工作空间!" << std::endl;
        return -1;
    }
    
    // 角度约束处理
    clampAngles(theta1, theta_min[0], theta_max[0]);
    clampAngles(theta2, theta_min[1], theta_max[1]);
    clampAngles(d3, theta_min[2], theta_max[2]);
    clampAngles(theta4, theta_min[3], theta_max[3]);
    
    // 正解验证
    Pose actual = forwardKinematics(theta1, theta2, d3, theta4);
    std::cout << "位置误差: (" 
              << target.x - actual.x << ", " 
              << target.y - actual.y << ", " 
              << target.z - actual.z << ")" << std::endl;
              
    return 0;
}

五、测试验证方法

void testWorkspace() {
    // 生成工作空间网格点
    for(double x = -0.5; x <= 0.5; x += 0.1) {
        for(double y = -0.4; y <= 0.4; y += 0.1) {
            Pose target = {x, y, 0.1, 0.0};
            double theta1, theta2, d3, theta4;
            bool success = inverseKinematics(target, theta1, theta2, d3, theta4);
            std::cout << "点("<< x << ","<< y << ") 可达: " 
                      << (success ? "是" : "否") << std::endl;
        }
    }
}

参考代码 4轴scara机器人的正逆解代码 www.youwenfan.com/contentcnh/56976.html

六、扩展功能实现

1. 三维空间扩展

// 添加俯仰角控制
struct Pose3D {
    double x, y, z;
    double yaw, pitch;  // 新增俯仰角
};

// 修改正运动学方程
pose3D forwardKinematics3D(double theta1, double theta2, 
                           double d3, double theta4, double theta5) {
    // 增加俯仰角计算
    double pitch = theta5;
    // ... 其他计算
}

2. 动力学补偿

// 添加重力补偿项
void gravityCompensation(double& torque1, double& torque2) {
    static const double m = 1.2;  // 末端质量
    static const double g = 9.81;
    torque1 += m * g * L1 * sin(theta1);
    torque2 += m * g * (L1 * sin(theta1) + L2 * sin(theta1 + theta2));
}

七、参考文献

  1. SCARA机器人正运动学公式推导
  2. 解析法逆解实现细节
  3. 工业级运动控制实现方案
  4. 多解选择策略与优化

建议结合具体机械结构参数调整DH参数,并通过实际标定优化模型精度。对于实时控制系统,推荐使用C++实现并配合实时操作系统(RTOS)。

posted @ 2025-09-23 11:54  躲雨小伙  阅读(65)  评论(0)    收藏  举报