{"uid":"cap_hwYBwbI4Vexdr3g6qFYYa","slug":"halowerk-opencv-robot-hand-eye-calibration-f7c280af","name":"HALOWERK OpenCV Robot Hand-Eye Calibration","description":"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.","url":"https://medien.halowerk.com/v1/oss-opencv-robot-hand-eye-calibrate?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"gripper_to_base":{"type":"array","items":{"type":"array","items":{"type":"array","items":{"type":"number","maximum":1000000000,"minimum":-1000000000},"maxItems":4,"minItems":4},"maxItems":4,"minItems":4},"maxItems":32,"minItems":3},"target_to_camera":{"type":"array","items":{"type":"array","items":{"type":"array","items":{"type":"number","maximum":1000000000,"minimum":-1000000000},"maxItems":4,"minItems":4},"maxItems":4,"minItems":4},"maxItems":32,"minItems":3}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.003","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.003/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.003","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.003","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_3e_TSrPXuNDMIcjxe2KFZ","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.003","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Computes the rigid camera-to-gripper transform from synchronized gripper-to-base and target-to-camera pose pairs using OpenCV hand-eye calibration","exampleAgentPrompt":"I have 10 synchronized pose pairs from my robot arm — the gripper-to-base 4x4 matrices and the matching target-to-camera 4x4 matrices — can you run hand-eye calibration to figure out the rigid transform between the camera and the gripper?","exampleUseCases":[{"title":"Eye-in-hand pick-and-place setup","prompt":"I'm setting up a robot arm with a wrist-mounted camera for pick-and-place. I've recorded 8 synchronized gripper-to-base and target-to-camera 4x4 pose matrices while moving the arm. Can you calibrate and give me the camera-to-gripper transform so the robot knows where the camera is?"},{"title":"Verify new camera mount alignment","prompt":"We just remounted the camera on our robot gripper and need to recheck the hand-eye transform. Here are 12 gripper-to-base poses and 12 matching target-to-camera poses from our calibration run — please compute the updated camera-to-gripper rigid transform."},{"title":"Automated calibration pipeline for robot fleet","prompt":"I'm building an automated calibration workflow for multiple robot arms. For each robot I'll pass in a set of at least 5 gripper-to-base and target-to-camera 4x4 transformation matrices — run the hand-eye calibration and return the camera-to-gripper transform for each one."}],"resultDescription":"Returns the recovered 4x4 rigid transformation matrix representing the constant camera-to-gripper (or gripper-to-camera) transform, enabling the robot to map camera observations into the robot's coordinate frame.","failureModes":["Fewer than 3 pose pairs provided — minimum 3 required","Mismatched array lengths between gripper_to_base and target_to_camera — pairs must correspond exactly","Off-by-one synchronization error in input poses produces a plausible but entirely incorrect transform with no detectable error signal","Non-rigid or degenerate motion between poses causes numerically unstable calibration","Malformed 4x4 matrix (wrong dimensions) returns a validation error","Insufficient motion diversity in the pose sequence leads to poorly conditioned solution"],"whenToPreferThis":"Choose this endpoint when you need a fast, pay-per-call hand-eye calibration computation backed by OpenCV without managing local dependencies. It is ideal for robotics pipelines that already collect synchronized pose data and need to periodically recompute the camera-to-gripper transform, especially in cloud-deployed or agent-driven automation workflows where installing OpenCV locally is impractical.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-30T19:05:28.144Z","isFirstParty":false,"canonicalSlug":"halowerk-opencv-robot-hand-eye-calibration-f7c280af"}