yangjames / calico

A visual-inertial calibration library designed for rapid problem construction and debugging.

Calico

Calico is a lightweight visual-inertial calibration library that allows for rapid problem construction, debugging, and tool creation. Unlike other codebases that are limited to standalone calibration tools for specific hardware setups, Calico is a flexible library that enables building and modifying custom tools to suit your hardware requirements. If your calibration problem aligns with our geometry paradigm, there is no need to modify the underlying optimization.

Calico features:

• Flexible auto-differentiable cost functors.
• Sensor intrinsics, extrinsics, and latency estimation.
• The ability to add multiple sensors.
• Measurement outlier tagging and exclusion.
• Per-sensor robustifier kernels.
• Ability to create custom sensor models.

Check out our wiki pages for more info.

License

Poor sensor calibration is a problem endemic to robotics, yet it's typically not given enough attention because it tends to detract from higher level project goals. The purpose of this library is to help roboticists quickly resolve their calibration issues so that they can move on to more interesting things. This library is hereby granted the MIT license, to be used free of charge by anyone within academia or industry.

To the best of my knowledge, all library dependencies also fall under BSD 2/3, LGPL, or Apache 2.0.

MIT License

Copyright (c) 2023 James Yang

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

calico's Issues

Create RigidBody struct

Contains member variables:

• absl::flat_hash_mapEigen::Vector3d model_points - model definition points for the fiducial.
• Pose of rigid body resolved in world frame as quaternion + translation
• bool model_points_are_constant - boolean indicating if the model points should be estimated
• bool world_pose_is_constant - boolean indicating if the rigid body pose should be estimated

Create BSpline class

Create Landmark struct

Contains the following member variables:

• Eigen::Vector3d world_point - landmark point resolved in the world frame
• int landmark_id - unique numerical id for the landmark
• bool point_is_constant - boolean indicator for if the point should be estimated

Create WorldModel class

Contains the following methods:

• AddLandmark - method for adding a landmark to the world model
• AddRigidBody - method for adding a rigid body to the world model
• AddParametersToProblem - Adds all landmarks and rigid bodies to a ceres problem as either free parameters or constants

Ubuntu 22 Deps Typo

Hello.

I believe bind11-dev should be pybind11-dev

Best.

Create initial camera model with forward and inverse projection methods

Create BatchOptimizer class

Contains the following methods:

• AddSensorRig - Adds a sensor rig to the optimization problem
• AddWorldModel - Adds world model to the optimization problem
• Optimize - Runs an optimization

Add feature for synthetic sensor measurement generation for unit testing

Any related paper ?

Create abstract sensor class

• Setter/getter for extrinsics parameters as a Pose object (quaternion + translation)
• Setter/getter for intrinsics parameters as a length n eigen vector
• Method for adding calibration parameters to a ceres problem