查看“自动识别托盘取放货”的源代码

<languages/>
== 概述 / Overview ==
"自动识别托盘取放货"是 [[Special:MyLanguage/自动识别工位并取放货|自动识别工位并取放货]] 的特例：工位本身是一个独立的托盘（pallet）而非固定货架，车体到位后通过激光雷达识别托盘的 ''两个插孔''（叉车场景）或 ''两个边缘特征''（顶升 / 平板场景），完成对位 + 升降 + 离场。

"Auto-pallet pick & place" specialises [[Special:MyLanguage/自动识别工位并取放货|station-aware pick & place]] to pallets. The "station" is the pallet itself, not a fixed rack. Once the vehicle is roughly in front, the lidar locates the pallet's '''two fork-pockets''' (forklifts) or its '''two side edges''' (lift / flat-bed vehicles), then the car runs the alignment / lift / withdraw sequence.

== 与货架取放的差异 / Difference from rack pick ==
{| class="wikitable"
! 项 / Item !! 货架（KIVA 类）/ Rack (KIVA) !! 托盘 / Pallet
|-
| 特征点 / Features || 4 条立腿 / 4 legs || 2 个叉孔或 2 条边 / 2 fork pockets or 2 edges
|-
| 进入方向 / Entry side || 任意（钻入式）/ any (slide-under) || 固定一侧（短边）/ fixed short edge
|-
| 升降高度 / Lift travel || 30–80 mm（顶升）/ 30–80 mm (jack) || 100–1800 mm（叉齿）/ 100–1800 mm (forks)
|-
| 误差容忍 / Tolerance || ±30 mm / ±2° || ±15 mm / ±1.5°（叉孔机械约束）
|-
| 主用 Movement || `AutoShelfFetching_ManyLegs` || `AutoFetchGood`, `PutGood`
|-
| 主用 Detector || `LidarDetectTray` (3-腿) / 4-腿 || `LidarDetectPallet`, `LidarBlobPairDetector`
|}

托盘场景对车体姿态的容忍度比货架低，因为叉齿与叉孔的机械配合余量只有 10–15 mm；调试时务必先用 [[Special:MyLanguage/标定与校准|标定与校准]] 把外参打齐。

Pallet pickup tolerates less pose error than rack pickup because the fork-pocket/fork-tine clearance is only 10–15 mm. Always level the lidar and verify extrinsics via [[Special:MyLanguage/标定与校准|the calibration guide]] before tuning.

== 工作流程 / Pipeline ==
# '''粗对位 / Coarse approach''': SimpleComposer 把 AGV 派到托盘前的 ''anchor 站点''，使用普通巡线 / 路径跟踪。<br />SimpleComposer dispatches the AGV to the anchor site in front of the pallet; ordinary line / path follow.
# '''粗检测 / Coarse detect''': 启动 `LidarDetectPallet`，从前方激光帧中找出托盘的两个特征（叉孔中心 or 边缘中点）的近似位置。<br />Start `LidarDetectPallet` to extract approximate centers of the two pallet features from one or two lidar frames.
# '''精对位跟踪 / Fine alignment''': 用检测出的两个点拟合托盘中轴线，`AutoFetchGood`（或 `PutGood`）开启跟踪，逼近期望停靠位姿。<br />Fit the pallet's midline from the two feature points; `AutoFetchGood` (or `PutGood`) opens a tracking thread to drive toward the docking pose.
# '''升降 / Lift''': 到位后通过 `[[Special:MyLanguage/Medulla-API|Medulla 上位 IO]]` 触发叉齿 / 顶升机构动作。<br />On dock, fire the fork / jack actuator through Medulla upper-IO.
# '''离场 / Withdraw''': 倒车（叉车）或推车前进（顶升）退出托盘正前方区域。<br />Reverse out (forklift) or roll forward (jack) to clear.

<syntaxhighlight lang="csharp">
public void PickPallet(double approachX, double approachY, double palletX, double palletY)
{
    Queue(
      async () =>
      {
          // 1. Coarse approach
          DriveTask.WaitDriveTask(new SteeringLineFollowing
          {
              srcX = currentX, srcY = currentY,
              dstX = approachX, dstY = approachY,
              basespeed = 800
          }.Follow());
      },
      async () =>
      {
          // 2 + 3. Detect + fine alignment (encapsulated in AutoFetchGood)
          DriveTask.WaitDriveTask(new AutoFetchGood
          {
              aX = approachX, aY = approachY,
              bX = palletX,   bY = palletY,
              initSpeed   = 500,
              inShelfSpeed= 150,
              stopDist    = 80,           // tight: pocket / tine clearance
              width       = 800           // pallet pocket span
          }.Get());
      },
      async () =>
      {
          // 4. Lift via Medulla upper-IO (fork at 200 mm)
          MedullaAPI.SetUpperIO("forkHeight", 200);
          await WaitForUpperIO("forkAtTarget", timeoutMs: 5000);
      },
      async () =>
      {
          // 5. Withdraw 1.5 m
          DriveTask.WaitDriveTask(new SteeringLineFollowingReverse
          {
              srcX = palletX, srcY = palletY,
              dstX = approachX, dstY = approachY,
              basespeed = 400
          }.ReverseFollow());
      });
}
</syntaxhighlight>

== 调试要点 / Tuning ==
* '''叉孔检测假阳性 / False positive on fork pockets''': 缩窄 `LidarDetectPallet.widthMin/widthMax` 区间至 ±50 mm。
* '''托盘姿态偏 / Pallet pose drift''': 检查激光雷达水平度，重做 [[Special:MyLanguage/标定激光雷达外参|外参标定]]。
* '''叉齿与叉孔刮擦 / Tines scrape pocket walls''': 适当增大 `stopDist`（保留 20–30 mm 余量），或把 `inShelfSpeed` 降到 100 mm/s。
* '''码垛环境光斑干扰 / Beam glints in stacking yards''': 给托盘正面贴一段宽 50 mm 的吸光胶带可显著改善。

== 相关页面 / See also ==
* [[Special:MyLanguage/自动识别工位并取放货|自动识别工位并取放货]]
* [[Special:MyLanguage/托盘识别|托盘识别]] — 检测器的纯算法细节
* [[Special:MyLanguage/使用叉车自动取托盘功能|使用叉车自动取托盘功能]] — 终端使用手册视角
* [[Special:MyLanguage/识别料框并堆垛拆垛|识别料框并堆垛拆垛]]

[[Category:运动控制使用手册]]