Medienwerk

oss opencv robot hand eye calibrate

Solves the hand-eye problem: given a series of gripper-to-base poses read from the robot and the matching target-to-camera poses seen by the camera, it recovers the rigid transform between camera and gripper that stays constant as the arm moves. This is what lets a robot act on what its camera sees. The poses must be genuinely synchronized — a pairing that is off by one sample produces a confident and entirely wrong transform, and nothing in the data reveals it.

POST https://medien.halowerk.com/v1/oss-opencv-robot-hand-eye-calibrate

Eingaben

Felder des veröffentlichten Eingabeschemas
Feld	Typ	Pflicht	Beschreibung
gripper_to_base	array	Ja
target_to_camera	array	Ja

Vollständiges Eingabeschema anzeigen

{
  "type": "object",
  "properties": {
    "gripper_to_base": {
      "type": "array",
      "items": {
        "type": "array",
        "items": {
          "type": "array",
          "items": {
            "type": "number",
            "minimum": -1000000000,
            "maximum": 1000000000
          },
          "minItems": 4,
          "maxItems": 4
        },
        "minItems": 4,
        "maxItems": 4
      },
      "minItems": 3,
      "maxItems": 32
    },
    "target_to_camera": {
      "type": "array",
      "items": {
        "type": "array",
        "items": {
          "type": "array",
          "items": {
            "type": "number",
            "minimum": -1000000000,
            "maximum": 1000000000
          },
          "minItems": 4,
          "maxItems": 4
        },
        "minItems": 4,
        "maxItems": 4
      },
      "minItems": 3,
      "maxItems": 32
    }
  },
  "required": [
    "gripper_to_base",
    "target_to_camera"
  ],
  "additionalProperties": false,
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "description": "Numeric JSON arrays only. Additionally enforce equal paired dimensions, nondegenerate geometry, maximum 32768 pixels/image, 131072 scalars/array, and 1048576 encoded bytes. No paths or network resources."
}

Originalschema öffnen

Veröffentlichtes Eingabebeispiel

{
  "gripper_to_base": [
    [
      [
        0.9883261643209938,
        -0.011898272648401948,
        0.15188753742995567,
        -0.1
      ],
      [
        0.02965868306845241,
        0.9928985120353282,
        -0.11520810438800028,
        -0.08
      ],
      [
        -0.14943813247359922,
        0.11836796824316773,
        0.981660465057439,
        0.9
      ],
      [
        0,
        0,
        0,
        1
      ]
    ],
    [
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        0.9900332889206209,
        0.07810864350797697,
        0.11718842365337251,
        -0.08
      ],
      [
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        -0.06
      ],
      [
        -0.09983341664682815,
        -0.19767681165408388,
        0.975170327201816,
        1.1
      ],
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        0,
        0,
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        1
      ]
    ],
    [
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        0.9838313410528056,
        -0.13931586755647624,
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      ],
      [
        -0.14276370081881548,
        0.9794224989256464,
        0.1426537567916039,
        -0.1
      ],
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        0.29552020666133955,
        -0.09537450575679464,
        0.9505637859220634,
        0.8
      ],
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        0,
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    ],
    [
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      ],
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    ],
    [
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        0.9684764438206882,
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      ],
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      ],
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        0.95
      ],
      [
        0,
        0,
        0,
        1
      ]
    ]
  ],
  "target_to_camera": [
    [
      [
        0.9063237102581435,
        0.33288469091973355,
        0.26031733475738106,
        0.5204232013800494
      ],
      [
        -0.3848000025265721,
        0.9047162386004,
        0.1828045012254741,
        -0.09917100092930925
      ],
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        -0.17466050005500083,
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        0.9480598080060768,
        0.25671815524783104
      ],
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        0,
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        1
      ]
    ],
    [
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        0.9222283210537701,
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        0.2905690861056643,
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      ],
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      ],
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      ],
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    [
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        0.9685694851402569,
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    ],
    [
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        0.8732504913062019,
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        0.14998223097999983,
        0.49446971179787524
      ],
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        -0.4872295048277384,
        0.834827570239529,
        0.25626224379194174,
        -0.2805429704181118
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        0.08983366223433209
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    [
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        0.9229723671601914,
        0.36672150886044824,
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        0.4715357954702587
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    ]
  ]
}

Ergebnis & Dokumentation

Veröffentlichtes Ergebnisschema anzeigen

{
  "$ref": "https://medien.halowerk.com/v1/oss-opencv-robot-hand-eye-calibrate/schema#/outputSchema"
}

Veröffentlichtes Ergebnisbeispiel öffnen

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oss opencv robot hand eye calibrate

Eingaben

Veröffentlichtes Eingabebeispiel

Ergebnis & Dokumentation

Weitere Endpunkte dieses Hubs

ad detect

audio concat

audio convert