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// 机器人视觉高级(v56.0.0)
// 视觉伺服、物体抓取、SLAM增强、3D重建、机械臂控制、移动机器人导航
///|
/// 机器人视觉任务类型
pub(all) enum RobotVisionTaskType {
VisualServoing
ObjectGrasping
SLAMEnhanced
Reconstruction3D
ArmControl
MobileNavigation
HumanRobotInteraction
Unknown
} derive(Eq)
///|
/// 视觉伺服类型
pub(all) enum VisualServoingType {
PositionBased
ImageBased
Hybrid
Advanced
Unknown
} derive(Eq)
///|
/// 抓取类型
pub(all) enum GraspType {
ParallelJaw
SuctionCup
MultiFinger
Hook
Magnetic
Unknown
} derive(Eq)
///|
/// 机器人类型
pub(all) enum RobotType {
Manipulator
MobileRobot
Humanoid
Drone
Wheeled
Legged
Unknown
} derive(Eq)
///|
/// 物体位姿
pub(all) struct ObjectPose {
position : Array[Double]
orientation : Array[Double]
confidence : Double
object_id : Int
coordinate_frame : String
}
///|
/// 抓取配置
pub(all) struct GraspConfig {
grasp_type : GraspType
grasp_position : Array[Double]
grasp_orientation : Array[Double]
approach_direction : Array[Double]
grasp_width : Double
grasp_force : Double
pre_grasp_distance : Double
post_grasp_distance : Double
is_force_closure : Bool
quality_score : Double
}
///|
/// 关节状态
pub(all) struct JointState {
joint_names : Array[String]
joint_positions : Array[Double]
joint_velocities : Array[Double]
joint_efforts : Array[Double]
num_joints : Int
timestamp : Double
}
///|
/// 末端执行器状态
pub(all) struct EndEffectorState {
position : Array[Double]
orientation : Array[Double]
velocity : Array[Double]
angular_velocity : Array[Double]
force : Array[Double]
torque : Array[Double]
is_in_contact : Bool
contact_force : Double
}
///|
/// 轨迹点
pub(all) struct TrajectoryPoint {
joint_positions : Array[Double]
joint_velocities : Array[Double]
joint_accelerations : Array[Double]
end_effector_pose : ObjectPose
time_from_start : Double
}
///|
/// 规划轨迹
pub(all) struct RobotTrajectory {
points : Array[TrajectoryPoint]
num_points : Int
duration : Double
is_collision_free : Bool
is_singularity_free : Bool
planning_time : Double
planner_type : String
}
///|
/// 点云数据
pub(all) struct PointCloudData {
points : Array[Array[Double]]
colors : Array[Array[Int]]
normals : Array[Array[Double]]
num_points : Int
width : Int
height : Int
is_dense : Bool
coordinate_frame : String
}
///|
/// 网格数据
pub(all) struct MeshData {
vertices : Array[Array[Double]]
faces : Array[Array[Int]]
normals : Array[Array[Double]]
uv_coords : Array[Array[Double]]
num_vertices : Int
num_faces : Int
volume : Double
surface_area : Double
}
///|
/// 机器人视觉配置
pub(all) struct RobotVisionConfig {
task_type : RobotVisionTaskType
robot_type : RobotType
visual_servoing_type : VisualServoingType
grasp_type : GraspType
num_joints : Int
end_effector_type : String
camera_intrinsics : Array[Double]
camera_extrinsics : Array[Double]
hand_eye_transform : Array[Double]
control_frequency : Int
planning_time_limit : Double
collision_margin : Double
singularity_threshold : Double
use_force_control : Bool
use_visual_servoing : Bool
use_realtime : Bool
}
///|
/// 创建默认机器人视觉配置
pub fn create_default_robot_vision_config() -> RobotVisionConfig {
RobotVisionConfig::{
task_type: RobotVisionTaskType::ObjectGrasping,
robot_type: RobotType::Manipulator,
visual_servoing_type: VisualServoingType::ImageBased,
grasp_type: GraspType::ParallelJaw,
num_joints: 6,
end_effector_type: "parallel_jaw",
camera_intrinsics: [500.0, 0.0, 320.0, 0.0, 500.0, 240.0, 0.0, 0.0, 1.0],
camera_extrinsics: [
1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0,
],
hand_eye_transform: [
1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0,
],
control_frequency: 100,
planning_time_limit: 5.0,
collision_margin: 0.05,
singularity_threshold: 0.01,
use_force_control: true,
use_visual_servoing: true,
use_realtime: false,
}
}
///|
/// 估计物体位姿(简化版)
pub fn estimate_object_pose(
object_id : Int,
bounding_box : Array[Double],
depth_image : Array[Double],
config : RobotVisionConfig,
) -> ObjectPose {
// 简化的位姿估计:基于边界框和深度
let cx = (bounding_box[0] + bounding_box[2]) / 2.0
let cy = (bounding_box[1] + bounding_box[3]) / 2.0
let fx = config.camera_intrinsics[0]
let fy = config.camera_intrinsics[4]
let px = config.camera_intrinsics[2]
let py = config.camera_intrinsics[5]
let depth_idx = cy.to_int() * 640 + cx.to_int()
let depth = if depth_idx < depth_image.length() {
depth_image[depth_idx]
} else {
1.0
}
let x = (cx - px) * depth / fx
let y = (cy - py) * depth / fy
let z = depth
ObjectPose::{
position: [x, y, z],
orientation: [0.0, 0.0, 0.0, 1.0],
confidence: 0.85,
object_id,
coordinate_frame: "camera",
}
}
///|
/// 规划抓取(简化版)
pub fn plan_grasp(
object_pose : ObjectPose,
object_dimensions : Array[Double],
config : RobotVisionConfig,
) -> GraspConfig {
// 简化的抓取规划:从顶部抓取
let grasp_position = object_pose.position
let approach_direction = [0.0, 0.0, -1.0]
let grasp_width = object_dimensions[0] * 1.1
let grasp_force = 10.0
GraspConfig::{
grasp_type: config.grasp_type,
grasp_position,
grasp_orientation: [0.0, 0.0, 0.0, 1.0],
approach_direction,
grasp_width,
grasp_force,
pre_grasp_distance: 0.1,
post_grasp_distance: 0.1,
is_force_closure: true,
quality_score: 0.8,
}
}
///|
/// 规划机械臂轨迹(简化版)
pub fn plan_arm_trajectory(
start_pose : ObjectPose,
goal_pose : ObjectPose,
config : RobotVisionConfig,
) -> RobotTrajectory {
let points : Array[TrajectoryPoint] = []
let num_points = 50
for i in 0..<num_points {
let t = i.to_double() / (num_points - 1).to_double()
let position : Array[Double] = []
position.push(
start_pose.position[0] +
(goal_pose.position[0] - start_pose.position[0]) * t,
)
position.push(
start_pose.position[1] +
(goal_pose.position[1] - start_pose.position[1]) * t,
)
position.push(
start_pose.position[2] +
(goal_pose.position[2] - start_pose.position[2]) * t,
)
let joint_positions : Array[Double] = []
for _ in 0..<config.num_joints {
joint_positions.push(0.0)
}
let point = TrajectoryPoint::{
joint_positions,
joint_velocities: [],
joint_accelerations: [],
end_effector_pose: ObjectPose::{
position,
orientation: goal_pose.orientation,
confidence: 1.0,
object_id: 0,
coordinate_frame: "base",
},
time_from_start: t * 5.0,
}
points.push(point)
}
RobotTrajectory::{
points,
num_points,
duration: 5.0,
is_collision_free: true,
is_singularity_free: true,
planning_time: 0.5,
planner_type: "RRTConnect",
}
}
///|
/// 视觉伺服控制(简化版)
pub fn visual_servoing(
current_pose : ObjectPose,
desired_pose : ObjectPose,
config : RobotVisionConfig,
) -> Array[Double] {
ignore(config)
// 简化的视觉伺服:计算位置误差并生成控制量
let error : Array[Double] = []
error.push(desired_pose.position[0] - current_pose.position[0])
error.push(desired_pose.position[1] - current_pose.position[1])
error.push(desired_pose.position[2] - current_pose.position[2])
// 简单的比例控制
let kp = 0.5
let control : Array[Double] = []
control.push(error[0] * kp)
control.push(error[1] * kp)
control.push(error[2] * kp)
control
}
///|
/// 生成点云(简化版)
pub fn generate_point_cloud(
depth_image : Array[Double],
rgb_image : Array[Array[Int]],
config : RobotVisionConfig,
) -> PointCloudData {
ignore(rgb_image)
let points : Array[Array[Double]] = []
let colors : Array[Array[Int]] = []
let normals : Array[Array[Double]] = []
let fx = config.camera_intrinsics[0]
let fy = config.camera_intrinsics[4]
let px = config.camera_intrinsics[2]
let py = config.camera_intrinsics[5]
let width = 640
let height = 480
let mut state = 42
for v in 0..<height {
if v % 10 == 0 {
for u in 0..<width {
if u % 10 == 0 {
let idx = v * width + u
if idx < depth_image.length() {
let depth = depth_image[idx]
if depth > 0.0 && depth < 10.0 {
let x = (u.to_double() - px) * depth / fx
let y = (v.to_double() - py) * depth / fy
let z = depth
let point : Array[Double] = []
point.push(x)
point.push(y)
point.push(z)
points.push(point)
state = (state * 11035 + 12345) % 1000000
let color : Array[Int] = []
color.push(state % 256)
state = (state * 11035 + 12345) % 1000000
color.push(state % 256)
state = (state * 11035 + 12345) % 1000000
color.push(state % 256)
colors.push(color)
let normal : Array[Double] = []
normal.push(0.0)
normal.push(0.0)
normal.push(1.0)
normals.push(normal)
}
}
}
}
}
}
PointCloudData::{
points,
colors,
normals,
num_points: points.length(),
width,
height,
is_dense: false,
coordinate_frame: "camera",
}
}
///|
/// 生成机器人视觉报告
pub fn robot_vision_report_to_string(
task_type : RobotVisionTaskType,
config : RobotVisionConfig,
result_description : String,
) -> String {
let mut report = "## 机器人视觉高级报告\n\n"
report = report + "### 任务信息\n\n"
report = report + "| 指标 | 值 |\n|------|------|\n"
report = report +
"| 任务类型 | " +
(match task_type {
RobotVisionTaskType::VisualServoing => "视觉伺服"
RobotVisionTaskType::ObjectGrasping => "物体抓取"
RobotVisionTaskType::SLAMEnhanced => "SLAM增强"
RobotVisionTaskType::Reconstruction3D => "3D重建"
RobotVisionTaskType::ArmControl => "机械臂控制"
RobotVisionTaskType::MobileNavigation => "移动机器人导航"
RobotVisionTaskType::HumanRobotInteraction => "人机交互"
_ => "未知"
}) +
" |\n"
report = report +
"| 机器人类型 | " +
(match config.robot_type {
RobotType::Manipulator => "机械臂"
RobotType::MobileRobot => "移动机器人"
RobotType::Humanoid => "人形机器人"
RobotType::Drone => "无人机"
RobotType::Wheeled => "轮式"
RobotType::Legged => "腿式"
_ => "未知"
}) +
" |\n"
report = report +
"| 视觉伺服类型 | " +
(match config.visual_servoing_type {
VisualServoingType::PositionBased => "基于位置"
VisualServoingType::ImageBased => "基于图像"
VisualServoingType::Hybrid => "混合"
_ => "未知"
}) +
" |\n"
report = report +
"| 抓取类型 | " +
(match config.grasp_type {
GraspType::ParallelJaw => "平行夹爪"
GraspType::SuctionCup => "吸盘"
GraspType::MultiFinger => "多指"
GraspType::Hook => "钩子"
GraspType::Magnetic => "磁吸"
_ => "未知"
}) +
" |\n"
report = report + "| 关节数 | " + config.num_joints.to_string() + " |\n"
report = report +
"| 控制频率 | " +
config.control_frequency.to_string() +
" Hz |\n"
report = report +
"| 规划时间限制 | " +
config.planning_time_limit.to_string() +
" s |\n"
report = report +
"| 碰撞余量 | " +
config.collision_margin.to_string() +
" m |\n"
report = report + "\n### 结果\n\n"
report = report + result_description + "\n"
report
}