Deepen AI

Global Optimiser

Introduction

The API requires the client to upload the configuration for Global Optimisation in a zip file (.zip extension) in the format defined below. The contents of the zip file are called a dataset.

  1. The client makes a loop_optimisation API call, which runs the loop optimisation algorithm on the calibrations for the given configuration.

  2. The calibration process is completed without errors if the Loop optimisation API call response contains each calibration-id with updated extrinsics and the before and after residual error of the loop

Folder Structure

config.json contains configuration details of the loop_optimisation (dataset_ids_for_loop_optimisation, lambda_val, renamed_sensor_names and optimisation_name)

Note

The name of the JSON file should be config.json (case sensitive)

config.json 

{
    "dataset_ids_for_loop_optimisation":
    [
        "NiTWuK7hYsl03dmnSXmWQ282",
        "HOb2cM5FZ1yRQUHCHupDz79y",
        "CBLukrd36IsAX75hwEDKKOWz"
    ],
    "lambda_val": 1,
    "optimisation_name": "Demo_optimisation",
    "renamed_sensor_names":
    {
        "NiTWuK7hYsl03dmnSXmWQ282":
        [
            "s1",
            "s2"
        ],
        "HOb2cM5FZ1yRQUHCHupDz79y":
        [
            "s2",
            "s3"
        ],
        "CBLukrd36IsAX75hwEDKKOWz":
        [
            "s3",
            "s1"
        ]
    }
}

Sample config.json

config.json key description

Quick start

Before invoking the APIs, the client must obtain the clientId and auth token from Deepen AI. If you are a calibration admin, you can create different Access Tokens using the UI and use those instead. clientId is part of the path parameters in most API calls, and the auth token should be prefixed with “Bearer” and passed to the ‘Authorization’ header in all API requests. How to get Access Tokens can be found on the following link: Access token for APIs

Loop Optimisation

This POST API call sends a zip file to the server and runs the loop optimisation algorithm. As the response, it returns the updated extrinsics and the residual error before the optimisation and after the optimisation to the user.

https://tools.calibrate.deepen.ai/api/v2/external/clients/{clientId}/loop_optimisation

Request

Path parameters

Body

Response

{
    "6QIA43UWNwdiks85lHnAc2da": {
        "original_extrinsics": {
            "roll": -91.51176360979406,
            "pitch": -0.7853331754606847,
            "yaw": -89.73580857135546,
            "px": 0.06297976077742809,
            "py": -0.2671144409542271,
            "pz": -0.06347677696290424
        },
        "optimised_extrinsics": {
            "roll": -162.78830086097742,
            "pitch": -67.70468852329144,
            "yaw": -67.75615602883266,
            "px": -0.16792771218395555,
            "py": -0.17175453956126496,
            "pz": -0.15735750873866253
        },
        "first_sensor": "s3",
        "second_sensor": "s1",
        "calibration_type": "lidar_camera_calibration"
    },
    "DIjnSTbKZ9gsci7uy5iQfHCu": {
        "original_extrinsics": {
            "roll": 1.2714894839312245,
            "pitch": -0.7715740726838012,
            "yaw": 3.757236823512545,
            "px": -0.05193859737110649,
            "py": 0.796489794765278,
            "pz": 0.023697180957906575
        },
        "optimised_extrinsics": {
            "roll": 32.69493047307559,
            "pitch": -24.39224818371977,
            "yaw": 2.684326464767165,
            "px": -0.06294408225362882,
            "py": 0.6277749217995089,
            "pz": 0.31418121569303137
        },
        "first_sensor": "s1",
        "second_sensor": "s2",
        "calibration_type": "multi_lidar_calibration"
    },
    "chTmOKGvF9LeY6PiOEObFwJr": {
        "original_extrinsics": {
            "roll": -91.37613268811,
            "pitch": 0.6464214970125648,
            "yaw": -85.92938066631706,
            "px": 0.027734081727064118,
            "py": 0.5336431958220468,
            "pz": -0.043782383437678325
        },
        "optimised_extrinsics": {
            "roll": -136.1776408027225,
            "pitch": -58.7953465856894,
            "yaw": -98.3309580011168,
            "px": 0.4195387376287298,
            "py": 0.23897812124162132,
            "pz": 0.3203764330895245
        },
        "first_sensor": "s2",
        "second_sensor": "s3",
        "calibration_type": "lidar_camera_calibration"
    },
    "residual_error": [
        {
            "before": {
                "roll": 75.1373056595837,
                "pitch": -87.81393486062242,
                "yaw": 12.955394128297483,
                "px": 0.0080040164755718,
                "py": -0.32501818030990653,
                "pz": 0.20784293571718906
            },
            "after": {
                "roll": 1.6803259056739946e-14,
                "pitch": 6.519136608525574e-16,
                "yaw": 2.178289900990984e-16,
                "px": 4.163336342344337e-17,
                "py": 0.0,
                "pz": 1.3877787807814457e-17
            }
        }
    ]
}
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