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pick_ik repository

Repository Summary

Checkout URI https://github.com/PickNikRobotics/pick_ik.git
VCS Type git
VCS Version main
Last Updated 2024-09-30
Dev Status DEVELOPED
CI status No Continuous Integration
Released RELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Packages

Name Version
pick_ik 1.1.0

README

pick_ik

pick_ik is an inverse kinematics (IK) solver compatible with MoveIt 2.

The solver is a reimplementation of bio_ik, which combines:

  • A local optimizer which solves inverse kinematics via gradient descent
  • A global optimizer based on evolutionary algorithms

Critically, pick_ik allows you to specify custom cost functions as discussed in this paper, so you can prioritize additional objectives than simply solving inverse kinematics at a specific frame. For example, you can minimize joint displacement from the initial guess, enforce that joints are close to a particular pose, or even pass custom cost functions to the plugin.

If you are familiar with bio_ik, the functionality in this package includes:

  • Reimplementation of the memetic solver (equivalent to bio1 and bio2_memetic solvers)
  • Reimplementation of the numeric gradient descent solvers (equivalent to gd, gd_r, and gd_c solvers)
  • Fully configurable number of threads if using the global solver
  • Cost functions on joint displacement, joint centering, and avoiding joint limits

For more details on the implementation, take a look at the paper or the full thesis.


Getting Started

To get started using pick_ik, refer to the following README files:

CONTRIBUTING

No CONTRIBUTING.md found.

Repository Summary

Checkout URI https://github.com/PickNikRobotics/pick_ik.git
VCS Type git
VCS Version main
Last Updated 2024-09-30
Dev Status DEVELOPED
CI status No Continuous Integration
Released RELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Packages

Name Version
pick_ik 1.1.0

README

pick_ik

pick_ik is an inverse kinematics (IK) solver compatible with MoveIt 2.

The solver is a reimplementation of bio_ik, which combines:

  • A local optimizer which solves inverse kinematics via gradient descent
  • A global optimizer based on evolutionary algorithms

Critically, pick_ik allows you to specify custom cost functions as discussed in this paper, so you can prioritize additional objectives than simply solving inverse kinematics at a specific frame. For example, you can minimize joint displacement from the initial guess, enforce that joints are close to a particular pose, or even pass custom cost functions to the plugin.

If you are familiar with bio_ik, the functionality in this package includes:

  • Reimplementation of the memetic solver (equivalent to bio1 and bio2_memetic solvers)
  • Reimplementation of the numeric gradient descent solvers (equivalent to gd, gd_r, and gd_c solvers)
  • Fully configurable number of threads if using the global solver
  • Cost functions on joint displacement, joint centering, and avoiding joint limits

For more details on the implementation, take a look at the paper or the full thesis.


Getting Started

To get started using pick_ik, refer to the following README files:

CONTRIBUTING

No CONTRIBUTING.md found.

Repository Summary

Checkout URI https://github.com/PickNikRobotics/pick_ik.git
VCS Type git
VCS Version main
Last Updated 2024-09-30
Dev Status DEVELOPED
CI status No Continuous Integration
Released RELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Packages

Name Version
pick_ik 1.1.0

README

pick_ik

pick_ik is an inverse kinematics (IK) solver compatible with MoveIt 2.

The solver is a reimplementation of bio_ik, which combines:

  • A local optimizer which solves inverse kinematics via gradient descent
  • A global optimizer based on evolutionary algorithms

Critically, pick_ik allows you to specify custom cost functions as discussed in this paper, so you can prioritize additional objectives than simply solving inverse kinematics at a specific frame. For example, you can minimize joint displacement from the initial guess, enforce that joints are close to a particular pose, or even pass custom cost functions to the plugin.

If you are familiar with bio_ik, the functionality in this package includes:

  • Reimplementation of the memetic solver (equivalent to bio1 and bio2_memetic solvers)
  • Reimplementation of the numeric gradient descent solvers (equivalent to gd, gd_r, and gd_c solvers)
  • Fully configurable number of threads if using the global solver
  • Cost functions on joint displacement, joint centering, and avoiding joint limits

For more details on the implementation, take a look at the paper or the full thesis.


Getting Started

To get started using pick_ik, refer to the following README files:

CONTRIBUTING

No CONTRIBUTING.md found.

Repository Summary

Checkout URI https://github.com/PickNikRobotics/pick_ik.git
VCS Type git
VCS Version main
Last Updated 2024-09-30
Dev Status DEVELOPED
CI status No Continuous Integration
Released RELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Packages

Name Version
pick_ik 1.1.0

README

pick_ik

pick_ik is an inverse kinematics (IK) solver compatible with MoveIt 2.

The solver is a reimplementation of bio_ik, which combines:

  • A local optimizer which solves inverse kinematics via gradient descent
  • A global optimizer based on evolutionary algorithms

Critically, pick_ik allows you to specify custom cost functions as discussed in this paper, so you can prioritize additional objectives than simply solving inverse kinematics at a specific frame. For example, you can minimize joint displacement from the initial guess, enforce that joints are close to a particular pose, or even pass custom cost functions to the plugin.

If you are familiar with bio_ik, the functionality in this package includes:

  • Reimplementation of the memetic solver (equivalent to bio1 and bio2_memetic solvers)
  • Reimplementation of the numeric gradient descent solvers (equivalent to gd, gd_r, and gd_c solvers)
  • Fully configurable number of threads if using the global solver
  • Cost functions on joint displacement, joint centering, and avoiding joint limits

For more details on the implementation, take a look at the paper or the full thesis.


Getting Started

To get started using pick_ik, refer to the following README files:

CONTRIBUTING

No CONTRIBUTING.md found.