Robotic Control Interface & Manipulation Planning Library
This is a python library to operate a real or simulated robot, work with robot/world configurations, compute differentiable features, formulate and solve constrained optimization problems (for inverse kinematics, path optimization, and manipulation planning), and interfacing to various physical simulation engines. These python bindings were developed for easier access to the underlying C++ code base, esp. for teaching and students. This code base is how we, in the Learning & Intelligent Systems Lab, operate our robots.
Library Sources: https://github.com/MarcToussaint/robotic/
Tutorial Notebooks: https://github.com/MarcToussaint/rai-tutorials/
Contents:
- Getting Started
- Tutorials
- Intro: Configurations
- Intro: BotOp (Robot Operation) interface
- Grasp Test
- Intro: KOMO - Motion Optimization
- BotOp-2: Real robot operation checklist & first steps
- Config-2: Computing differentiable features & collision evaluation
- Config-3: Importing, editing & manipulating them
- KOMO-2: Reporting & explaining convergence
- KOMO-3: Manipulation Modelling & Execution
- LGP-1: First Mini Interface
- Extension - Simulation: Low-level stepping interface & gym environments
- Extension - Rendering: Basic opengl, offscreen (headless), and interface to physics-based rendering
- Extension - RRT: basic finding example
- Extension - NLP interface: Low-level NLP formulation and solving
- Extension - Gym Environment Interface: minimal example
- Lecture Script
- robotic python API
ArgWordBotOpCameraViewConfigConfigurationViewerControlModeFSFrameJTKOMOLGP_ToolLogic2KOMO_TranslatorNLPNLP_FactoryNLP_SamplerNLP_SolverNLP_SolverIDNLP_SolverOptionsOTPathFinderSTSYSimulationSimulationEngineSolverReturnTAMP_Providercompiled()default_Logic2KOMO_Translator()default_TAMP_Provider()depthImage2PointCloud()params_add()params_clear()params_file()params_print()raiPath()setRaiPath()