BranchesTags

Repository files navigation

Approximate Inverse Kinematics

Build Status

Implementation of an approximate inverse kinematics for robots described by URDF files in C++ with Python bindings. The approximate IK allows you to set a weight for the position and the orientation to define how important it is to reach them. Typically it is more important to reach the position exactly than the orientation. Sometimes there are situations where it is not even possible to reach the position at all while ignoring the orientation. In these cases we want to find the IK solution that is closest to the desired goal.

We achieve these features by defining a cost function that has a weight for the position and the orientation constraint respectively and lets the choice of the weight for the user. We solve the IK problem by optimizing the cost function with respect to the joint angles with L-BFGS-B, a local optimizer that respects boundaries (i.e. joint limits). The required derivatives are calculated numerically which is usually fast enough.

Installation

Standalone

Install the dependencies and install the C++ header:

mkdir build
cd build
cmake ..
make install

Now you can use

#include <approxik/approxik.hpp>

in your project.

Python Bindings

./get_dependencies.sh
mkdir build
cd build
cmake ..
cd ../python
sudo python setup.py install

Note that dependencies will be installed in the subfolders deps/install. Source the env.sh to set the correct environment variables.

Folders

  • approxik: C++ implementation (in one header file)
  • cmake: additional CMake modules
  • data: contains data files (e.g. URDFs, trajectories)
  • deps: dependencies
  • evaluation: scripts to generate plots for the paper
  • examples: several scripts for visualization of the approximate IK approach
  • paper: summary of the method, experiments, etc.
  • prototype: first prototype of the approximate IK
  • python: Python wrapper for C++ implementation
  • src: C++ example program
  • test: unit tests

About

Approximate Inverse Kinematics

Topics

approximationcplusplusinverse-kinematicsoptimizationpythonrobotics

Resources

Readme
License
Activity
Custom properties

Stars

3 stars

Watchers

1 watching

Forks

0 forks
Report repository

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

Skip to content
BranchesTags
Repository files navigation
Approximate Inverse Kinematics
Build Status
Implementation of an approximate inverse kinematics for robots described by
URDF files in C++ with Python bindings. The approximate IK allows you to set
a weight for the position and the orientation to define how important it is
to reach them. Typically it is more important to reach the position exactly
than the orientation. Sometimes there are situations where it is not even
possible to reach the position at all while ignoring the orientation. In these
cases we want to find the IK solution that is closest to the desired goal.
We achieve these features by defining a cost function that has a weight for
the position and the orientation constraint respectively and lets the choice
of the weight for the user. We solve the IK problem by optimizing the cost
function with respect to the joint angles with L-BFGS-B, a local optimizer
that respects boundaries (i.e. joint limits). The required derivatives are
calculated numerically which is usually fast enough.
Installation
Standalone
Install the dependencies and install the C++ header:
mkdir build
cd build
cmake ..
make install

Now you can use
#include <approxik/approxik.hpp>

in your project.
Python Bindings
./get_dependencies.sh
mkdir build
cd build
cmake ..
cd ../python
sudo python setup.py install

Note that dependencies will be installed in the subfolders deps/install.
Source the env.sh to set the correct environment variables.
Folders
  • approxik: C++ implementation (in one header file)
  • cmake: additional CMake modules
  • data: contains data files (e.g. URDFs, trajectories)
  • deps: dependencies
  • evaluation: scripts to generate plots for the paper
  • examples: several scripts for visualization of the approximate IK approach
  • paper: summary of the method, experiments, etc.
  • prototype: first prototype of the approximate IK
  • python: Python wrapper for C++ implementation
  • src: C++ example program
  • test: unit tests
About
Approximate Inverse Kinematics
Topics
approximationcplusplusinverse-kinematicsoptimizationpythonrobotics
Resources
Readme
License
Activity
Custom properties
Stars
3 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Approximate Inverse Kinematics
Build Status
Implementation of an approximate inverse kinematics for robots described by
URDF files in C++ with Python bindings. The approximate IK allows you to set
a weight for the position and the orientation to define how important it is
to reach them. Typically it is more important to reach the position exactly
than the orientation. Sometimes there are situations where it is not even
possible to reach the position at all while ignoring the orientation. In these
cases we want to find the IK solution that is closest to the desired goal.
We achieve these features by defining a cost function that has a weight for
the position and the orientation constraint respectively and lets the choice
of the weight for the user. We solve the IK problem by optimizing the cost
function with respect to the joint angles with L-BFGS-B, a local optimizer
that respects boundaries (i.e. joint limits). The required derivatives are
calculated numerically which is usually fast enough.
Installation
Standalone
Install the dependencies and install the C++ header:
mkdir build
cd build
cmake ..
make install

Now you can use
#include <approxik/approxik.hpp>

in your project.
Python Bindings
./get_dependencies.sh
mkdir build
cd build
cmake ..
cd ../python
sudo python setup.py install

Note that dependencies will be installed in the subfolders deps/install.
Source the env.sh to set the correct environment variables.
Folders
  • approxik: C++ implementation (in one header file)
  • cmake: additional CMake modules
  • data: contains data files (e.g. URDFs, trajectories)
  • deps: dependencies
  • evaluation: scripts to generate plots for the paper
  • examples: several scripts for visualization of the approximate IK approach
  • paper: summary of the method, experiments, etc.
  • prototype: first prototype of the approximate IK
  • python: Python wrapper for C++ implementation
  • src: C++ example program
  • test: unit tests
About
Approximate Inverse Kinematics
Topics
approximationcplusplusinverse-kinematicsoptimizationpythonrobotics
Resources
Readme
License
Activity
Custom properties
Stars
3 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Approximate Inverse Kinematics
Build Status
Implementation of an approximate inverse kinematics for robots described by
URDF files in C++ with Python bindings. The approximate IK allows you to set
a weight for the position and the orientation to define how important it is
to reach them. Typically it is more important to reach the position exactly
than the orientation. Sometimes there are situations where it is not even
possible to reach the position at all while ignoring the orientation. In these
cases we want to find the IK solution that is closest to the desired goal.
We achieve these features by defining a cost function that has a weight for
the position and the orientation constraint respectively and lets the choice
of the weight for the user. We solve the IK problem by optimizing the cost
function with respect to the joint angles with L-BFGS-B, a local optimizer
that respects boundaries (i.e. joint limits). The required derivatives are
calculated numerically which is usually fast enough.
Installation
Standalone
Install the dependencies and install the C++ header:
mkdir build
cd build
cmake ..
make install

Now you can use
#include <approxik/approxik.hpp>

in your project.
Python Bindings
./get_dependencies.sh
mkdir build
cd build
cmake ..
cd ../python
sudo python setup.py install

Note that dependencies will be installed in the subfolders deps/install.
Source the env.sh to set the correct environment variables.
Folders
  • approxik: C++ implementation (in one header file)
  • cmake: additional CMake modules
  • data: contains data files (e.g. URDFs, trajectories)
  • deps: dependencies
  • evaluation: scripts to generate plots for the paper
  • examples: several scripts for visualization of the approximate IK approach
  • paper: summary of the method, experiments, etc.
  • prototype: first prototype of the approximate IK
  • python: Python wrapper for C++ implementation
  • src: C++ example program
  • test: unit tests
About
Approximate Inverse Kinematics
Topics
approximationcplusplusinverse-kinematicsoptimizationpythonrobotics
Resources
Readme
License
Activity
Custom properties
Stars
3 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

Skip to content
BranchesTags
Repository files navigation
Approximate Inverse Kinematics
Build Status
Implementation of an approximate inverse kinematics for robots described by
URDF files in C++ with Python bindings. The approximate IK allows you to set
a weight for the position and the orientation to define how important it is
to reach them. Typically it is more important to reach the position exactly
than the orientation. Sometimes there are situations where it is not even
possible to reach the position at all while ignoring the orientation. In these
cases we want to find the IK solution that is closest to the desired goal.
We achieve these features by defining a cost function that has a weight for
the position and the orientation constraint respectively and lets the choice
of the weight for the user. We solve the IK problem by optimizing the cost
function with respect to the joint angles with L-BFGS-B, a local optimizer
that respects boundaries (i.e. joint limits). The required derivatives are
calculated numerically which is usually fast enough.
Installation
Standalone
Install the dependencies and install the C++ header:
mkdir build
cd build
cmake ..
make install

Now you can use
#include <approxik/approxik.hpp>

in your project.
Python Bindings
./get_dependencies.sh
mkdir build
cd build
cmake ..
cd ../python
sudo python setup.py install

Note that dependencies will be installed in the subfolders deps/install.
Source the env.sh to set the correct environment variables.
Folders
  • approxik: C++ implementation (in one header file)
  • cmake: additional CMake modules
  • data: contains data files (e.g. URDFs, trajectories)
  • deps: dependencies
  • evaluation: scripts to generate plots for the paper
  • examples: several scripts for visualization of the approximate IK approach
  • paper: summary of the method, experiments, etc.
  • prototype: first prototype of the approximate IK
  • python: Python wrapper for C++ implementation
  • src: C++ example program
  • test: unit tests
About
Approximate Inverse Kinematics
Topics
approximationcplusplusinverse-kinematicsoptimizationpythonrobotics
Resources
Readme
License
Activity
Custom properties
Stars
3 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Approximate Inverse Kinematics
Build Status
Implementation of an approximate inverse kinematics for robots described by
URDF files in C++ with Python bindings. The approximate IK allows you to set
a weight for the position and the orientation to define how important it is
to reach them. Typically it is more important to reach the position exactly
than the orientation. Sometimes there are situations where it is not even
possible to reach the position at all while ignoring the orientation. In these
cases we want to find the IK solution that is closest to the desired goal.
We achieve these features by defining a cost function that has a weight for
the position and the orientation constraint respectively and lets the choice
of the weight for the user. We solve the IK problem by optimizing the cost
function with respect to the joint angles with L-BFGS-B, a local optimizer
that respects boundaries (i.e. joint limits). The required derivatives are
calculated numerically which is usually fast enough.
Installation
Standalone
Install the dependencies and install the C++ header:
mkdir build
cd build
cmake ..
make install

Now you can use
#include <approxik/approxik.hpp>

in your project.
Python Bindings
./get_dependencies.sh
mkdir build
cd build
cmake ..
cd ../python
sudo python setup.py install

Note that dependencies will be installed in the subfolders deps/install.
Source the env.sh to set the correct environment variables.
Folders
  • approxik: C++ implementation (in one header file)
  • cmake: additional CMake modules
  • data: contains data files (e.g. URDFs, trajectories)
  • deps: dependencies
  • evaluation: scripts to generate plots for the paper
  • examples: several scripts for visualization of the approximate IK approach
  • paper: summary of the method, experiments, etc.
  • prototype: first prototype of the approximate IK
  • python: Python wrapper for C++ implementation
  • src: C++ example program
  • test: unit tests
About
Approximate Inverse Kinematics
Topics
approximationcplusplusinverse-kinematicsoptimizationpythonrobotics
Resources
Readme
License
Activity
Custom properties
Stars
3 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Approximate Inverse Kinematics
Build Status
Implementation of an approximate inverse kinematics for robots described by
URDF files in C++ with Python bindings. The approximate IK allows you to set
a weight for the position and the orientation to define how important it is
to reach them. Typically it is more important to reach the position exactly
than the orientation. Sometimes there are situations where it is not even
possible to reach the position at all while ignoring the orientation. In these
cases we want to find the IK solution that is closest to the desired goal.
We achieve these features by defining a cost function that has a weight for
the position and the orientation constraint respectively and lets the choice
of the weight for the user. We solve the IK problem by optimizing the cost
function with respect to the joint angles with L-BFGS-B, a local optimizer
that respects boundaries (i.e. joint limits). The required derivatives are
calculated numerically which is usually fast enough.
Installation
Standalone
Install the dependencies and install the C++ header:
mkdir build
cd build
cmake ..
make install

Now you can use
#include <approxik/approxik.hpp>

in your project.
Python Bindings
./get_dependencies.sh
mkdir build
cd build
cmake ..
cd ../python
sudo python setup.py install

Note that dependencies will be installed in the subfolders deps/install.
Source the env.sh to set the correct environment variables.
Folders
  • approxik: C++ implementation (in one header file)
  • cmake: additional CMake modules
  • data: contains data files (e.g. URDFs, trajectories)
  • deps: dependencies
  • evaluation: scripts to generate plots for the paper
  • examples: several scripts for visualization of the approximate IK approach
  • paper: summary of the method, experiments, etc.
  • prototype: first prototype of the approximate IK
  • python: Python wrapper for C++ implementation
  • src: C++ example program
  • test: unit tests
About
Approximate Inverse Kinematics
Topics
approximationcplusplusinverse-kinematicsoptimizationpythonrobotics
Resources
Readme
License
Activity
Custom properties
Stars
3 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

Skip to content
BranchesTags
Repository files navigation
Approximate Inverse Kinematics
Build Status
Implementation of an approximate inverse kinematics for robots described by
URDF files in C++ with Python bindings. The approximate IK allows you to set
a weight for the position and the orientation to define how important it is
to reach them. Typically it is more important to reach the position exactly
than the orientation. Sometimes there are situations where it is not even
possible to reach the position at all while ignoring the orientation. In these
cases we want to find the IK solution that is closest to the desired goal.
We achieve these features by defining a cost function that has a weight for
the position and the orientation constraint respectively and lets the choice
of the weight for the user. We solve the IK problem by optimizing the cost
function with respect to the joint angles with L-BFGS-B, a local optimizer
that respects boundaries (i.e. joint limits). The required derivatives are
calculated numerically which is usually fast enough.
Installation
Standalone
Install the dependencies and install the C++ header:
mkdir build
cd build
cmake ..
make install

Now you can use
#include <approxik/approxik.hpp>

in your project.
Python Bindings
./get_dependencies.sh
mkdir build
cd build
cmake ..
cd ../python
sudo python setup.py install

Note that dependencies will be installed in the subfolders deps/install.
Source the env.sh to set the correct environment variables.
Folders
  • approxik: C++ implementation (in one header file)
  • cmake: additional CMake modules
  • data: contains data files (e.g. URDFs, trajectories)
  • deps: dependencies
  • evaluation: scripts to generate plots for the paper
  • examples: several scripts for visualization of the approximate IK approach
  • paper: summary of the method, experiments, etc.
  • prototype: first prototype of the approximate IK
  • python: Python wrapper for C++ implementation
  • src: C++ example program
  • test: unit tests
About
Approximate Inverse Kinematics
Topics
approximationcplusplusinverse-kinematicsoptimizationpythonrobotics
Resources
Readme
License
Activity
Custom properties
Stars
3 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages