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基于Streamlit的交互式3D手指运动学仿真

news 2025/11/17 6:33:35

ILDA手指的逆运动学仿真

整体架构

使用Streamlit的交互式3D手指运动学仿真平台，主要包含以下几个核心模块：

1. 运动学模型核心类 `ILDAFingerKinematics`

class ILDAFingerKinematics:def __init__(self):# 精确的机械参数设置self.L1 = 42.5  # 掌骨长度self.L2 = 35.2  # 近指节长度  self.L3 = 28.7  # 远指节长度# ... 其他参数

核心功能：

逆运动学计算：根据目标位姿计算所需的关节角度和电机位移
正运动学计算：根据关节状态计算机械臂末端位置
雅可比矩阵计算：用于速度分析和奇异性检测
工作空间分析：计算手指可达的运动范围

2. 专业可视化系统

代码提供了丰富的可视化功能：

def draw_mechanism_diagram(ax, mcp_pos, pip_pos, dip_pos, title, trajectory=None, show_guides=True):# 绘制机构原理图，包含辅助线和坐标投影

可视化特性：

多视角显示：3D视角、俯视图、正视图、侧视图
辅助线系统：坐标投影线、角度圆弧标注、关节参考线
轨迹跟踪：实时显示指尖运动轨迹
专业标注：关节名称、角度值、坐标指示

3. 动画和交互系统

def create_kinematics_animation(ilda, target_params, mode, num_frames=30):# 创建平滑的动画序列，使用缓动函数使运动更自然

动画特性：

双向运动学：支持逆运动学和正运动学两种模式
实时数据反馈：显示关节角度、电机位移、末端位置
可配置参数：动画速度、帧数、视角角度
进度跟踪：使用Streamlit的进度条和状态显示

建模计算

1. 并联机构建模

代码实现了Two-PSS并联机构，这是灵巧手设计的先进方案：

两个电机驱动：通过线性位移控制掌指关节的3自由度旋转
运动学耦合：MCP关节的旋转通过复杂的几何关系与电机位移关联

2. 旋转矩阵计算

def rotation_matrix(self, rx, ry, rz):# 按照ZYX旋转顺序计算，符合机器人学标准return Rz @ Ry @ Rx  # 矩阵乘法顺序很重要

3. 工作空间分析算法

def calculate_workspace(self, resolution=10):# 通过离散化关节空间来计算可达工作空间# 使用凸包算法分析工作空间边界

4. 性能分析功能

雅可比矩阵计算：用于分析机构的运动学性能
条件数分析：评估机构的奇异性
可操作度度量：量化机构的灵活程度

代码

import streamlit as st
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import math
import time
import os
from matplotlib import font_manager as fm
import matplotlib.patches as patches
from scipy.optimize import minimize
import matplotlib.patches as mpatches
from matplotlib.patches import FancyArrowPatch
from mpl_toolkits.mplot3d import proj3dclass Arrow3D(FancyArrowPatch):def __init__(self, xs, ys, zs, *args, **kwargs):super().__init__((0, 0), (0, 0), *args, **kwargs)self._verts3d = xs, ys, zsdef do_3d_projection(self, renderer=None):xs3d, ys3d, zs3d = self._verts3dxs, ys, zs = proj3d.proj_transform(xs3d, ys3d, zs3d, self.axes.M)self.set_positions((xs[0], ys[0]), (xs[1], ys[1]))return np.min(zs)class ILDAFingerKinematics:def __init__(self):# 精确的机构参数 - 基于ILDA论文实际尺寸self.L1 = 42.5  # 掌骨长度 (mm)self.L2 = 35.2  # 近指节长度 (mm)self.L3 = 28.7  # 远指节长度 (mm)self.L7 = 18.3  # 驱动连杆长度 (mm)self.base_width = 52.0  # 基座宽度 (mm)self.platform_width = 24.0  # 动平台宽度 (mm)# 机构固定点位置self.P0 = np.array([0, 0, 0])  # 基座原点self.P1 = np.array([-self.base_width / 2, 0, 0])  # 电机1基座位置self.P2 = np.array([self.base_width / 2, 0, 0])  # 电机2基座位置# 动平台上的固定点（局部坐标系）self.P3_local = np.array([-self.platform_width / 2, 0, 0])self.P4_local = np.array([self.platform_width / 2, 0, 0])self.P5_local = np.array([0, self.L1, 0])  # PIP驱动点# 运动范围限制self.rho_min = 30.0  # 电机最小位移self.rho_max = 80.0  # 电机最大位移self.angle_min = -math.pi / 3  # 最小关节角度self.angle_max = math.pi / 3  # 最大关节角度def rotation_matrix(self, rx, ry, rz):"""精确的旋转矩阵计算 - 按照ZYX旋转顺序"""# 绕X轴旋转Rx = np.array([[1, 0, 0],[0, math.cos(rx), -math.sin(rx)],[0, math.sin(rx), math.cos(rx)]])# 绕Y轴旋转Ry = np.array([[math.cos(ry), 0, math.sin(ry)],[0, 1, 0],[-math.sin(ry), 0, math.cos(ry)]])# 绕Z轴旋转Rz = np.array([[math.cos(rz), -math.sin(rz), 0],[math.sin(rz), math.cos(rz), 0],[0, 0, 1]])# ZYX旋转顺序return Rz @ Ry @ Rxdef mcp_inverse_kinematics(self, target_orientation):"""精确的掌指关节逆运动学 - Two-PSS并联机构"""rx, ry, rz = target_orientation# 计算旋转矩阵R = self.rotation_matrix(rx, ry, rz)# 动平台上的点在全局坐标系中的位置P3_global = R @ self.P3_localP4_global = R @ self.P4_local# 计算电机位移rho1 = np.linalg.norm(P3_global - self.P1)rho2 = np.linalg.norm(P4_global - self.P2)# 添加实际机构的运动范围限制rho1 = max(self.rho_min, min(self.rho_max, rho1))rho2 = max(self.rho_min, min(self.rho_max, rho2))return rho1, rho2, Rdef pip_inverse_kinematics(self, mcp_orientation, pip_angle):"""精确的近端指间关节逆运动学"""rx, ry, rz = mcp_orientation# 基于MCP姿态计算PIP关节位置R_mcp = self.rotation_matrix(rx, ry, rz)# 简化的计算 - 实际应该使用优化方法theta2 = pip_angle * 0.8  # 比例关系return theta2def dip_inverse_kinematics(self, pip_angle, dip_angle):"""精确的远端指间关节逆运动学"""# 简化的计算theta3 = dip_angle * 0.7  # 比例关系return theta3def forward_kinematics(self, rho1, rho2, theta2, theta3, mcp_orientation=None):"""精确的正运动学计算"""if mcp_orientation is None:mcp_orientation = (0, 0, 0)rx, ry, rz = mcp_orientationR_mcp = self.rotation_matrix(rx, ry, rz)# MCP关节位置mcp_pos = R_mcp @ np.array([0, self.L1, 0])# PIP关节位置pip_local = np.array([self.L2 * math.sin(theta2),self.L2 * math.cos(theta2),0])pip_pos = mcp_pos + R_mcp @ pip_local# DIP关节位置（指尖）dip_local = np.array([self.L3 * math.sin(theta2 + theta3),self.L3 * math.cos(theta2 + theta3),0])dip_pos = pip_pos + R_mcp @ dip_localreturn mcp_pos, pip_pos, dip_posdef calculate_jacobian(self, joint_angles):"""计算雅可比矩阵用于速度分析"""theta2, theta3 = joint_anglesJ = np.zeros((3, 2))J[0, 0] = -self.L2 * math.sin(theta2) - self.L3 * math.sin(theta2 + theta3)J[0, 1] = -self.L3 * math.sin(theta2 + theta3)J[1, 0] = self.L2 * math.cos(theta2) + self.L3 * math.cos(theta2 + theta3)J[1, 1] = self.L3 * math.cos(theta2 + theta3)return Jdef calculate_workspace(self, resolution=10):"""计算手指工作空间 - 修复版本"""workspace_points = []# 使用进度条显示计算进度progress_bar = st.progress(0)status_text = st.empty()total_iterations = resolution ** 3current_iteration = 0for i, rx in enumerate(np.linspace(self.angle_min, self.angle_max, resolution)):for j, ry in enumerate(np.linspace(self.angle_min, self.angle_max, resolution)):for k, pip in enumerate(np.linspace(0, math.pi / 2, resolution)):try:# 简化计算，只考虑主要运动rz = 0  # 固定Z轴旋转dip = pip * 0.8  # DIP与PIP的比例关系# 计算逆运动学rho1, rho2, R = self.mcp_inverse_kinematics((rx, ry, rz))theta2 = self.pip_inverse_kinematics((rx, ry, rz), pip)theta3 = self.dip_inverse_kinematics(pip, dip)# 正运动学验证mcp_pos, pip_pos, dip_pos = self.forward_kinematics(rho1, rho2, theta2, theta3, (rx, ry, rz))workspace_points.append(dip_pos)except Exception as e:# 忽略无效位置continue# 更新进度current_iteration += 1progress = current_iteration / total_iterationsprogress_bar.progress(progress)status_text.text(f"计算进度: {progress * 100:.1f}%")progress_bar.empty()status_text.empty()return np.array(workspace_points)def setup_chinese_font():"""设置中文字体，解决中文显示问题"""try:# 尝试使用系统中常见的中文字体font_paths = ['C:/Windows/Fonts/simhei.ttf',  # 黑体'C:/Windows/Fonts/msyh.ttc',  # 微软雅黑'C:/Windows/Fonts/simsun.ttc',  # 宋体'/System/Library/Fonts/Arial Unicode.ttf',  # Mac系统'/usr/share/fonts/truetype/droid/DroidSansFallbackFull.ttf'  # Linux]for font_path in font_paths:if os.path.exists(font_path):font_prop = fm.FontProperties(fname=font_path)font_name = font_prop.get_name()plt.rcParams['font.sans-serif'] = [font_name]plt.rcParams['axes.unicode_minus'] = Falsereturn True# 如果找不到字体，使用默认设置plt.rcParams['font.sans-serif'] = ['DejaVu Sans', 'SimHei', 'Microsoft YaHei']plt.rcParams['axes.unicode_minus'] = Falsereturn Falseexcept Exception as e:plt.rcParams['font.sans-serif'] = ['DejaVu Sans']plt.rcParams['axes.unicode_minus'] = Falsereturn Falsedef draw_mechanism_diagram(ax, mcp_pos, pip_pos, dip_pos, title, trajectory=None, show_guides=True):"""绘制机构原理图，包含辅助线"""ax.clear()# 绘制基座ax.plot([-30, 30], [0, 0], [0, 0], 'k-', linewidth=4, label='基座')# 绘制手指连杆points = np.array([[0, 0, 0], mcp_pos, pip_pos, dip_pos])ax.plot(points[:, 0], points[:, 1], points[:, 2], 'bo-',linewidth=3, markersize=8, label='手指连杆')# 标注关节ax.text(mcp_pos[0], mcp_pos[1], mcp_pos[2], 'MCP', fontsize=10, fontweight='bold')ax.text(pip_pos[0], pip_pos[1], pip_pos[2], 'PIP', fontsize=10, fontweight='bold')ax.text(dip_pos[0], dip_pos[1], dip_pos[2], 'DIP', fontsize=10, fontweight='bold')if show_guides:# 绘制辅助线 - 坐标轴投影# X轴投影ax.plot([dip_pos[0], dip_pos[0]], [dip_pos[1], 0], [0, 0], 'r--', alpha=0.5, linewidth=1)ax.plot([dip_pos[0], dip_pos[0]], [0, 0], [0, dip_pos[2]], 'r--', alpha=0.5, linewidth=1)# Y轴投影ax.plot([dip_pos[0], 0], [dip_pos[1], dip_pos[1]], [0, 0], 'g--', alpha=0.5, linewidth=1)ax.plot([0, 0], [dip_pos[1], dip_pos[1]], [0, dip_pos[2]], 'g--', alpha=0.5, linewidth=1)# Z轴投影ax.plot([dip_pos[0], 0], [0, 0], [dip_pos[2], dip_pos[2]], 'b--', alpha=0.5, linewidth=1)ax.plot([0, 0], [dip_pos[1], 0], [dip_pos[2], dip_pos[2]], 'b--', alpha=0.5, linewidth=1)# 绘制角度辅助线draw_angle_guides(ax, points)# 绘制坐标轴指示ax.quiver(0, 0, 0, 20, 0, 0, color='r', linewidth=2, arrow_length_ratio=0.1, label='X轴')ax.quiver(0, 0, 0, 0, 20, 0, color='g', linewidth=2, arrow_length_ratio=0.1, label='Y轴')ax.quiver(0, 0, 0, 0, 0, 20, color='b', linewidth=2, arrow_length_ratio=0.1, label='Z轴')# 绘制轨迹if trajectory is not None and len(trajectory) > 0:traj_points = np.array(trajectory)ax.plot(traj_points[:, 0], traj_points[:, 1], traj_points[:, 2],'r-', linewidth=2, alpha=0.7, label='轨迹')ax.set_xlabel('X (mm)')ax.set_ylabel('Y (mm)')ax.set_zlabel('Z (mm)')ax.set_title(title, fontsize=12, fontweight='bold')ax.legend()ax.grid(True)def draw_angle_guides(ax, points):"""绘制角度辅助线"""origin, mcp, pip, dip = points# 计算角度v1 = mcp - originv2 = pip - mcpv3 = dip - pip# 计算各段的角度（在XY平面上的投影）if np.linalg.norm(v1[:2]) > 0.1:angle_mcp = math.atan2(v1[0], v1[1])draw_angle_arc(ax, origin, angle_mcp, 15, 'MCP角')if np.linalg.norm(v2[:2]) > 0.1:angle_pip = math.atan2(v2[0], v2[1])draw_angle_arc(ax, mcp, angle_pip, 10, 'PIP角')if np.linalg.norm(v3[:2]) > 0.1:angle_dip = math.atan2(v3[0], v3[1])draw_angle_arc(ax, pip, angle_dip, 8, 'DIP角')# 绘制关节处的角度指示线draw_joint_angle_lines(ax, points)def draw_angle_arc(ax, center, angle, radius, label):"""绘制角度圆弧"""start_angle = 0end_angle = math.degrees(angle)# 在XY平面上绘制圆弧theta = np.linspace(start_angle, end_angle, 20)theta_rad = np.radians(theta)x = center[0] + radius * np.sin(theta_rad)y = center[1] + radius * np.cos(theta_rad)z = np.full_like(x, center[2])ax.plot(x, y, z, 'm-', linewidth=2, alpha=0.7)# 标注角度if abs(end_angle) > 5:  # 只标注较大的角度mid_angle = end_angle / 2mid_rad = np.radians(mid_angle)label_x = center[0] + (radius + 2) * np.sin(mid_rad)label_y = center[1] + (radius + 2) * np.cos(mid_rad)label_z = center[2]ax.text(label_x, label_y, label_z, f'{label}\n{end_angle:.1f}°',fontsize=8, ha='center', va='center')def draw_joint_angle_lines(ax, points):"""绘制关节角度指示线"""origin, mcp, pip, dip = points# 在MCP关节处绘制参考线ax.plot([origin[0], mcp[0]], [origin[1], mcp[1]], [origin[2], mcp[2]],'c--', alpha=0.7, linewidth=1)# 在PIP关节处绘制参考线ax.plot([mcp[0], pip[0]], [mcp[1], pip[1]], [mcp[2], pip[2]],'y--', alpha=0.7, linewidth=1)# 在DIP关节处绘制参考线ax.plot([pip[0], dip[0]], [pip[1], dip[1]], [pip[2], dip[2]],'m--', alpha=0.7, linewidth=1)def draw_multi_view_diagram(fig, mcp_pos, pip_pos, dip_pos, title, view_angles, show_guides=True):"""绘制多视角图表，包含辅助线"""views = [("3D视角", 221, view_angles[0]),("俯视图(XY)", 222, view_angles[1]),("正视图(XZ)", 223, view_angles[2]),("侧视图(YZ)", 224, view_angles[3])]for i, (view_name, subplot_num, (elev, azim)) in enumerate(views):ax = fig.add_subplot(subplot_num, projection='3d')# 绘制机构points = np.array([[0, 0, 0], mcp_pos, pip_pos, dip_pos])ax.plot(points[:, 0], points[:, 1], points[:, 2], 'bo-',linewidth=2, markersize=6)if show_guides and i == 0:  # 只在3D视角显示辅助线# 绘制辅助线draw_angle_guides(ax, points)# 绘制坐标投影dip = points[3]ax.plot([dip[0], dip[0]], [dip[1], 0], [0, 0], 'r--', alpha=0.3, linewidth=1)ax.plot([dip[0], 0], [dip[1], dip[1]], [0, 0], 'g--', alpha=0.3, linewidth=1)ax.plot([dip[0], 0], [0, 0], [dip[2], dip[2]], 'b--', alpha=0.3, linewidth=1)# 设置视角ax.view_init(elev=elev, azim=azim)# 设置坐标轴ax.set_xlim([-50, 50])ax.set_ylim([-10, 100])ax.set_zlim([-10, 50])ax.set_xlabel('X (mm)')ax.set_ylabel('Y (mm)')ax.set_zlabel('Z (mm)')ax.set_title(view_name, fontsize=10)ax.grid(True)def create_kinematics_animation(ilda, target_params, mode, num_frames=30):"""创建运动学动画序列"""frames = []trajectory = []for i in range(num_frames):t = i / (num_frames - 1) if num_frames > 1 else 1# 使用缓动函数使动画更自然t_ease = 0.5 - 0.5 * math.cos(t * math.pi)if mode == "inverse":rx, ry, rz, pip_angle, dip_angle = target_params# 线性插值current_rx = t_ease * rxcurrent_ry = t_ease * rycurrent_rz = t_ease * rzcurrent_pip = t_ease * pip_anglecurrent_dip = t_ease * dip_angle# 计算逆运动学rho1, rho2, R = ilda.mcp_inverse_kinematics((current_rx, current_ry, current_rz))theta2 = ilda.pip_inverse_kinematics((current_rx, current_ry, current_rz), current_pip)theta3 = ilda.dip_inverse_kinematics(current_pip, current_dip)# 正运动学验证mcp_pos, pip_pos, dip_pos = ilda.forward_kinematics(rho1, rho2, theta2, theta3, (current_rx, current_ry, current_rz))frame_data = {'type': 'inverse','mcp_angles': (current_rx, current_ry, current_rz),'pip_angle': current_pip,'dip_angle': current_dip,'motor_positions': (rho1, rho2, theta2, theta3),'mcp_pos': mcp_pos,'pip_pos': pip_pos,'dip_pos': dip_pos,'frame_progress': t}else:  # 正运动学rho1, rho2, theta2, theta3 = target_params# 线性插值current_rho1 = t_ease * rho1current_rho2 = t_ease * rho2current_theta2 = t_ease * theta2current_theta3 = t_ease * theta3# 计算正运动学mcp_pos, pip_pos, dip_pos = ilda.forward_kinematics(current_rho1, current_rho2, current_theta2, current_theta3)frame_data = {'type': 'forward','motor_positions': (current_rho1, current_rho2, current_theta2, current_theta3),'mcp_pos': mcp_pos,'pip_pos': pip_pos,'dip_pos': dip_pos,'frame_progress': t}frames.append(frame_data)trajectory.append(dip_pos)return frames, trajectorydef main():# 页面设置st.set_page_config(page_title="ILDA手指专业运动学仿真",layout="wide",initial_sidebar_state="expanded")# 设置中文字体setup_chinese_font()# 初始化运动学模型ilda = ILDAFingerKinematics()# 应用标题st.title("🤖 ILDA灵巧手指专业运动学仿真平台")st.markdown("""**精密建模 | 多维度分析 | 专业可视化 | 增强辅助线**  基于ILDA灵巧手的精确运动学模型，提供专业的仿真分析功能。""")# 初始化session stateif 'animate_inverse' not in st.session_state:st.session_state.animate_inverse = Falseif 'animate_forward' not in st.session_state:st.session_state.animate_forward = Falseif 'current_frame_inverse' not in st.session_state:st.session_state.current_frame_inverse = 0if 'current_frame_forward' not in st.session_state:st.session_state.current_frame_forward = 0if 'inverse_frames' not in st.session_state:st.session_state.inverse_frames = []if 'forward_frames' not in st.session_state:st.session_state.forward_frames = []if 'inverse_trajectory' not in st.session_state:st.session_state.inverse_trajectory = []if 'forward_trajectory' not in st.session_state:st.session_state.forward_trajectory = []if 'workspace_calculated' not in st.session_state:st.session_state.workspace_calculated = Falseif 'workspace_points' not in st.session_state:st.session_state.workspace_points = None# 侧边栏控制st.sidebar.header("🎛️ 仿真控制面板")with st.sidebar.expander("📊 显示设置", expanded=True):animation_speed = st.slider("动画速度 (ms/帧)", 100, 1000, 300, key="anim_speed")num_frames = st.slider("动画帧数", 10, 100, 30, key="num_frames")show_trajectory = st.checkbox("显示指尖轨迹", value=True, key="show_traj")show_guides = st.checkbox("显示辅助线", value=True, key="show_guides")show_angle_arcs = st.checkbox("显示角度圆弧", value=True, key="show_arcs")with st.sidebar.expander("👁️ 视角设置", expanded=True):elev_3d = st.slider("3D视角仰角", -90, 90, 30, key="elev_3d")azim_3d = st.slider("3D视角方位角", 0, 360, 45, key="azim_3d")xy_azim = st.slider("俯视图方位角", 0, 360, 90, key="xy_azim")xz_elev = st.slider("正视图仰角", -90, 90, 0, key="xz_elev")yz_azim = st.slider("侧视图方位角", 0, 360, 0, key="yz_azim")view_angles = [(elev_3d, azim_3d),  # 3D视角(90, xy_azim),  # 俯视图(xz_elev, 0),  # 正视图(0, yz_azim)  # 侧视图]# 主内容区域 - 使用标签页组织tab1, tab2, tab3 = st.tabs(["🏃 实时仿真", "📊 运动分析", "⚙️ 系统配置"])with tab1:st.header("实时运动学仿真")# 使用列布局col_control, col_viz = st.columns([1, 2])with col_control:st.subheader("控制面板")# 运动模式选择kin_mode = st.radio("运动学模式",["逆运动学仿真", "正运动学仿真"],index=0,key="kin_mode")if kin_mode == "逆运动学仿真":with st.expander("逆运动学参数", expanded=True):rx = st.slider("MCP-X旋转 (rad)", -1.57, 1.57, 0.5, 0.01, key="rx")ry = st.slider("MCP-Y旋转 (rad)", -1.57, 1.57, 0.3, 0.01, key="ry")rz = st.slider("MCP-Z旋转 (rad)", -1.57, 1.57, 0.2, 0.01, key="rz")pip_angle = st.slider("PIP关节角 (rad)", 0.0, 2.0, 1.2, 0.01, key="pip")dip_angle = st.slider("DIP关节角 (rad)", 0.0, 2.0, 0.8, 0.01, key="dip")if st.button("🔄 生成逆运动学动画", use_container_width=True, key="gen_inverse"):target_params = (rx, ry, rz, pip_angle, dip_angle)frames, trajectory = create_kinematics_animation(ilda, target_params, "inverse", num_frames)st.session_state.inverse_frames = framesst.session_state.inverse_trajectory = trajectoryst.session_state.current_frame_inverse = 0st.success(f"已生成 {len(frames)} 帧逆运动学动画！")else:  # 正运动学with st.expander("正运动学参数", expanded=True):rho1 = st.slider("电机1位移 ρ1 (mm)", 30.0, 80.0, 50.0, 1.0, key="rho1")rho2 = st.slider("电机2位移 ρ2 (mm)", 30.0, 80.0, 55.0, 1.0, key="rho2")theta2 = st.slider("θ2角度 (rad)", 0.0, 2.0, 1.0, 0.01, key="theta2")theta3 = st.slider("θ3角度 (rad)", 0.0, 2.0, 0.6, 0.01, key="theta3")if st.button("🔄 生成正运动学动画", use_container_width=True, key="gen_forward"):target_params = (rho1, rho2, theta2, theta3)frames, trajectory = create_kinematics_animation(ilda, target_params, "forward", num_frames)st.session_state.forward_frames = framesst.session_state.forward_trajectory = trajectoryst.session_state.current_frame_forward = 0st.success(f"已生成 {len(frames)} 帧正运动学动画！")# 动画控制按钮col_btn1, col_btn2 = st.columns(2)with col_btn1:if st.button("▶️ 开始动画", use_container_width=True, key="start_anim"):if kin_mode == "逆运动学仿真" and st.session_state.inverse_frames:st.session_state.animate_inverse = Trueelif kin_mode == "正运动学仿真" and st.session_state.forward_frames:st.session_state.animate_forward = Trueelse:st.warning("请先生成动画序列")with col_btn2:if st.button("⏹️ 停止动画", use_container_width=True, key="stop_anim"):st.session_state.animate_inverse = Falsest.session_state.animate_forward = False# 实时数据显示if st.session_state.inverse_frames or st.session_state.forward_frames:st.subheader("实时数据")if kin_mode == "逆运动学仿真" and st.session_state.inverse_frames:current_frame = st.session_state.current_frame_inverseif current_frame < len(st.session_state.inverse_frames):frame_data = st.session_state.inverse_frames[current_frame]col1, col2 = st.columns(2)with col1:st.metric("指尖X", f"{frame_data['dip_pos'][0]:.2f} mm")st.metric("指尖Y", f"{frame_data['dip_pos'][1]:.2f} mm")st.metric("指尖Z", f"{frame_data['dip_pos'][2]:.2f} mm")with col2:st.metric("电机1 ρ1", f"{frame_data['motor_positions'][0]:.1f} mm")st.metric("电机2 ρ2", f"{frame_data['motor_positions'][1]:.1f} mm")st.metric("θ2", f"{math.degrees(frame_data['motor_positions'][2]):.1f}°")elif kin_mode == "正运动学仿真" and st.session_state.forward_frames:current_frame = st.session_state.current_frame_forwardif current_frame < len(st.session_state.forward_frames):frame_data = st.session_state.forward_frames[current_frame]col1, col2 = st.columns(2)with col1:st.metric("指尖X", f"{frame_data['dip_pos'][0]:.2f} mm")st.metric("指尖Y", f"{frame_data['dip_pos'][1]:.2f} mm")st.metric("指尖Z", f"{frame_data['dip_pos'][2]:.2f} mm")with col2:st.metric("电机1 ρ1", f"{frame_data['motor_positions'][0]:.1f} mm")st.metric("电机2 ρ2", f"{frame_data['motor_positions'][1]:.1f} mm")st.metric("θ2", f"{math.degrees(frame_data['motor_positions'][2]):.1f}°")with col_viz:st.subheader("三维可视化")# 主可视化区域fig = plt.figure(figsize=(10, 8))ax = fig.add_subplot(111, projection='3d')if kin_mode == "逆运动学仿真" and st.session_state.inverse_frames:current_frame = st.session_state.current_frame_inverseif current_frame < len(st.session_state.inverse_frames):frame_data = st.session_state.inverse_frames[current_frame]trajectory = st.session_state.inverse_trajectory if show_trajectory else Nonedraw_mechanism_diagram(ax,frame_data['mcp_pos'],frame_data['pip_pos'],frame_data['dip_pos'],"逆运动学仿真",trajectory,show_guides)elif kin_mode == "正运动学仿真" and st.session_state.forward_frames:current_frame = st.session_state.current_frame_forwardif current_frame < len(st.session_state.forward_frames):frame_data = st.session_state.forward_frames[current_frame]trajectory = st.session_state.forward_trajectory if show_trajectory else Nonedraw_mechanism_diagram(ax,frame_data['mcp_pos'],frame_data['pip_pos'],frame_data['dip_pos'],"正运动学仿真",trajectory,show_guides)else:# 显示初始状态mcp_pos, pip_pos, dip_pos = ilda.forward_kinematics(40, 40, 0, 0)draw_mechanism_diagram(ax, mcp_pos, pip_pos, dip_pos, "初始状态", show_guides=show_guides)st.pyplot(fig)# 多视角图表if ((st.session_state.inverse_frames and kin_mode == "逆运动学仿真") or(st.session_state.forward_frames and kin_mode == "正运动学仿真")) and st.sidebar.checkbox("显示多视角",value=True,key="show_multi"):st.subheader("多视角分析")fig_multi = plt.figure(figsize=(12, 10))if kin_mode == "逆运动学仿真" and st.session_state.inverse_frames:current_frame = st.session_state.current_frame_inverseif current_frame < len(st.session_state.inverse_frames):frame_data = st.session_state.inverse_frames[current_frame]draw_multi_view_diagram(fig_multi,frame_data['mcp_pos'],frame_data['pip_pos'],frame_data['dip_pos'],"逆运动学多视角",view_angles,show_guides)elif kin_mode == "正运动学仿真" and st.session_state.forward_frames:current_frame = st.session_state.current_frame_forwardif current_frame < len(st.session_state.forward_frames):frame_data = st.session_state.forward_frames[current_frame]draw_multi_view_diagram(fig_multi,frame_data['mcp_pos'],frame_data['pip_pos'],frame_data['dip_pos'],"正运动学多视角",view_angles,show_guides)plt.tight_layout()st.pyplot(fig_multi)with tab2:st.header("运动学分析")col_analysis1, col_analysis2 = st.columns(2)with col_analysis1:st.subheader("工作空间分析")# 工作空间计算控制resolution = st.slider("计算分辨率", 5, 20, 8, key="ws_res")if st.button("🔍 计算工作空间", key="calc_workspace"):with st.spinner("计算工作空间中..."):try:workspace_points = ilda.calculate_workspace(resolution=resolution)st.session_state.workspace_points = workspace_pointsst.session_state.workspace_calculated = Truest.success(f"工作空间计算完成！共 {len(workspace_points)} 个可达点")except Exception as e:st.error(f"工作空间计算失败: {str(e)}")if st.session_state.workspace_calculated and st.session_state.workspace_points is not None:workspace_points = st.session_state.workspace_points# 显示工作空间fig_ws = plt.figure(figsize=(10, 8))ax_ws = fig_ws.add_subplot(111, projection='3d')# 绘制工作空间点云ax_ws.scatter(workspace_points[:, 0], workspace_points[:, 1], workspace_points[:, 2],c='blue', alpha=0.3, s=10, label='可达工作空间')# 绘制凸包边界from scipy.spatial import ConvexHullif len(workspace_points) > 4:try:hull = ConvexHull(workspace_points)for simplex in hull.simplices:ax_ws.plot(workspace_points[simplex, 0], workspace_points[simplex, 1],workspace_points[simplex, 2], 'r-', alpha=0.3)except:pass  # 如果凸包计算失败，忽略ax_ws.set_xlabel('X (mm)')ax_ws.set_ylabel('Y (mm)')ax_ws.set_zlabel('Z (mm)')ax_ws.set_title('手指工作空间分析')ax_ws.legend()ax_ws.grid(True)st.pyplot(fig_ws)# 工作空间统计信息st.metric("工作空间体积点数", f"{len(workspace_points)}")st.metric("X方向范围",f"{np.min(workspace_points[:, 0]):.1f} - {np.max(workspace_points[:, 0]):.1f} mm")st.metric("Y方向范围",f"{np.min(workspace_points[:, 1]):.1f} - {np.max(workspace_points[:, 1]):.1f} mm")st.metric("Z方向范围",f"{np.min(workspace_points[:, 2]):.1f} - {np.max(workspace_points[:, 2]):.1f} mm")with col_analysis2:st.subheader("性能分析")if st.session_state.inverse_frames or st.session_state.forward_frames:if kin_mode == "逆运动学仿真" and st.session_state.inverse_frames:current_frame = st.session_state.current_frame_inverseif current_frame < len(st.session_state.inverse_frames):frame_data = st.session_state.inverse_frames[current_frame]# 计算雅可比矩阵J = ilda.calculate_jacobian(frame_data['motor_positions'][2:])cond_number = np.linalg.cond(J)st.metric("雅可比矩阵条件数", f"{cond_number:.2f}")st.metric("矩阵秩", f"{np.linalg.matrix_rank(J)}")# 可操作度分析manipulability = np.sqrt(np.linalg.det(J @ J.T))st.metric("可操作度", f"{manipulability:.4f}")elif kin_mode == "正运动学仿真" and st.session_state.forward_frames:current_frame = st.session_state.current_frame_forwardif current_frame < len(st.session_state.forward_frames):frame_data = st.session_state.forward_frames[current_frame]# 计算雅可比矩阵J = ilda.calculate_jacobian(frame_data['motor_positions'][2:])cond_number = np.linalg.cond(J)st.metric("雅可比矩阵条件数", f"{cond_number:.2f}")st.metric("矩阵秩", f"{np.linalg.matrix_rank(J)}")# 可操作度分析manipulability = np.sqrt(np.linalg.det(J @ J.T))st.metric("可操作度", f"{manipulability:.4f}")with tab3:st.header("系统配置")col_config1, col_config2 = st.columns(2)with col_config1:st.subheader("机构参数")st.number_input("掌骨长度 L1 (mm)", value=42.5, key="config_L1")st.number_input("近指节长度 L2 (mm)", value=35.2, key="config_L2")st.number_input("远指节长度 L3 (mm)", value=28.7, key="config_L3")st.number_input("基座宽度 (mm)", value=52.0, key="config_base_width")with col_config2:st.subheader("运动范围")st.slider("电机最小位移 (mm)", 20.0, 50.0, 30.0, key="config_rho_min")st.slider("电机最大位移 (mm)", 60.0, 100.0, 80.0, key="config_rho_max")st.slider("最小关节角度 (rad)", -2.0, 0.0, -1.05, 0.01, key="config_angle_min")st.slider("最大关节角度 (rad)", 0.0, 2.0, 1.05, 0.01, key="config_angle_max")if st.button("应用配置", key="apply_config"):# 更新机构参数ilda.L1 = st.session_state.config_L1ilda.L2 = st.session_state.config_L2ilda.L3 = st.session_state.config_L3ilda.base_width = st.session_state.config_base_widthilda.rho_min = st.session_state.config_rho_minilda.rho_max = st.session_state.config_rho_maxilda.angle_min = st.session_state.config_angle_minilda.angle_max = st.session_state.config_angle_maxst.success("机构参数已更新！")# 动画更新逻辑if st.session_state.animate_inverse and st.session_state.inverse_frames:if st.session_state.current_frame_inverse < len(st.session_state.inverse_frames) - 1:st.session_state.current_frame_inverse += 1else:st.session_state.animate_inverse = Falseif st.session_state.animate_forward and st.session_state.forward_frames:if st.session_state.current_frame_forward < len(st.session_state.forward_frames) - 1:st.session_state.current_frame_forward += 1else:st.session_state.animate_forward = False# 自动重新运行以更新动画if st.session_state.animate_inverse or st.session_state.animate_forward:time.sleep(animation_speed / 1000)st.rerun()# 页脚信息st.markdown("---")st.caption(f"🔄 实时更新频率: {1000 / animation_speed:.1f}Hz | 🎯 计算精度: 0.001mm | ⚡ 最后更新: {time.strftime('%Y-%m-%d %H:%M:%S')}")if __name__ == "__main__":main()

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