#include <pinocchio/algorithm/kinematics.hpp>

// 正运动学计算
pinocchio::forwardKinematics(model, data, q);
data.oMi[joint_id]; // 获取关节i相对于基座的变换

import pinocchio as pin

# Python版本
pin.forwardKinematics(model, data, q)
data.oMi[joint_id]  # 获取关节变换

// 计算雅可比矩阵
pinocchio::computeJointJacobians(model, data);
pinocchio::getJointJacobian(model, data, joint_id, pinocchio::LOCAL, J);

# Python雅可比计算
pin.computeJointJacobians(model, data, q)
J = pin.getJointJacobian(model, data, joint_id, pin.LOCAL)

#include <pinocchio/algorithm/rnea.hpp>

// 计算关节力矩（递归牛顿欧拉算法）
Eigen::VectorXd tau = pinocchio::rnea(model, data, q, v, a);

# Python逆动力学
tau = pin.rnea(model, data, q, v, a)

#include <pinocchio/algorithm/aba.hpp>

// 计算关节加速度（Articulated Body算法）
Eigen::VectorXd a = pinocchio::aba(model, data, q, v, tau);

# Python正动力学
a = pin.aba(model, data, q, v, tau)

// 计算质量矩阵
pinocchio::crba(model, data, q); // Composite Rigid Body Algorithm
Eigen::MatrixXd M = data.M;

// 计算科里奥利、离心和重力项
pinocchio::nonLinearEffects(model, data, q, v);
Eigen::VectorXd nle = data.nle;

# Python动力学参数
M = pin.crba(model, data, q)  # 质量矩阵
nle = pin.nonLinearEffects(model, data, q, v)  # 非线性效应

// SE3变换
pinocchio::SE3 M(pinocchio::SE3::Random());
pinocchio::Motion v(pinocchio::Motion::Random());

// 变换操作
pinocchio::SE3 M2 = M * pinocchio::exp6(v);

# Python几何操作
M = pin.SE3.Random()
v = pin.Motion.Random()
M2 = M * pin.exp6(v)

# 更新包列表
sudo apt update

# 安装Pinocchio
sudo apt install libpinocchio-dev python3-pinocchio

# 安装Python绑定（如果单独安装）
pip install pin

# 安装依赖
sudo apt install cmake libeigen3-dev doxygen git

# 克隆源码
git clone --recursive https://github.com/stack-of-tasks/pinocchio.git
cd pinocchio

# 创建构建目录
mkdir build && cd build

# 配置和编译
cmake .. -DCMAKE_BUILD_TYPE=Release -DBUILD_UNIT_TESTS=OFF
make -j$(nproc)

# 安装
sudo make install

sudo apt install ros-$ROS_DISTRO-pinocchio

sudo apt install ros-$ROS_DISTRO-pinocchio

# 创建虚拟环境（推荐）
python3 -m venv pinocchio_env
source pinocchio_env/bin/activate

# 安装Python包
pip install pin notebook matplotlib numpy

#include <pinocchio/parsers/urdf.hpp>
#include <pinocchio/algorithm/kinematics.hpp>
#include <iostream>

int main() {
    // 创建模型
    pinocchio::Model model;
    pinocchio::urdf::buildModel("robot.urdf", model);

    // 创建数据结构
    pinocchio::Data data(model);

    // 定义关节配置
    Eigen::VectorXd q = pinocchio::neutral(model);

    // 计算正运动学
    pinocchio::forwardKinematics(model, data, q);

    // 输出末端执行器位置
    std::cout << "End-effector position: "
              << data.oMi[model.njoints-1].translation().transpose()
              << std::endl;

    return 0;
}

import pinocchio as pin
import numpy as np

# 加载机器人模型
model = pin.buildModelFromUrdf("robot.urdf")
data = model.createData()

# 定义关节配置
q = pin.neutral(model)

# 计算正运动学
pin.forwardKinematics(model, data, q)

# 获取末端执行器位置
end_effector_pose = data.oMi[model.njoints-1]
print(f"End-effector position: {end_effector_pose.translation.T}")

# 计算雅可比矩阵
pin.computeJointJacobians(model, data, q)
J = pin.getJointJacobian(model, data, model.njoints-1, pin.LOCAL)
print(f"Jacobian shape: {J.shape}")

// 自定义动力学算法
template<typename Scalar, int Options, template<typename,int> class JointCollectionTpl>
class CustomDynamics {
public:
    typedef pinocchio::ModelTpl<Scalar,Options,JointCollectionTpl> Model;
    typedef pinocchio::DataTpl<Scalar,Options,JointCollectionTpl> Data;

    void computeCustomAlgorithm(const Model& model, Data& data);
};

import cv2
import pinocchio as pin

# 视觉伺服应用
# 使用Pinocchio进行机器人运动学计算
# 使用OpenCV进行图像处理

import numpy as np
import scipy.optimize as opt
import pinocchio as pin

# 优化问题求解
def objective(q):
    pin.forwardKinematics(model, data, q)
    pose = data.oMi[end_effector_id]
    return np.sum((pose.translation - target_position)**2)

result = opt.minimize(objective, q0)

#include <omp.h>

// 并行动力学计算
void parallelDynamics(const std::vector<Eigen::VectorXd>& q_vector) {
    #pragma omp parallel for
    for(size_t i = 0; i < q_vector.size(); ++i) {
        pinocchio::forwardKinematics(model, data, q_vector[i]);
        // 处理结果
    }
}

# 解决方案：确保依赖项完整
sudo apt install build-essential cmake libeigen3-dev

# 解决方案：检查Python路径
export PYTHONPATH=$PYTHONPATH:/usr/local/lib/python3/dist-packages

# 解决方案：使用预编译的函数
pin.computeAllTerms(model, data, q, v)  # 一次性计算所有量

# 解决方案：重用Data对象
static pinocchio::Data data(model);  // 静态分配

<!-- 确保URDF格式正确 -->
<robot name="my_robot">
  <link name="base_link">
    <!-- 链接定义 -->
  </link>
  <joint name="joint1" type="revolute">
    <!-- 关节定义 -->
  </joint>
</robot>