lfd: cba | lfd_common
Stack Summary
Learning from Demonstration algorithms developed by the RAIL research group at WPI.
- Author: Maintained by Russell Toris
- License: BSD
- Repository: wpi-rail-ros-pkg
- Source: git https://github.com/WPI-RAIL/wpi-rail-ros-pkg
Documentation
Robot Learning from Demonstration (LfD) research focuses on algorithms that enable a robot to learn new task policies from demonstrations performed by a human teacher. The lfd ROS stack contains implementations of LfD used and developed by the RAIL research group at WPI. Currently, the classification based Confidence-Based Autonomy (CBA) algorithm is available via the cba package. |
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For additional details on LfD, please refer to the following publication:
Brenna Argall, Sonia Chernova, Manuela Veloso and Brett Browning. A Survey of Robot Learning from Demonstration. Robotics and Autonomous Systems. Vol. 57, No. 5, pages 469-483, 2009. PDF
Installation
To install the lfd stack, simply run the following commands in your shell:
1 cd /path/to/your/ros/stacks
2 git clone git://github.com/WPI-RAIL/wpi-rail-ros-pkg.git
3 cd wpi-rail-ros-pkg/lfd
4 rosdep install lfd
5 rosmake lfd
Startup
Packages may contain test nodes which can be launched with their respective .launch files. Additional information on how to run each algorithm is discussed in their respective package wiki pages. Tutorials and example uses of these algorithms will be arriving shortly.
Support
Please feel free to contact me at any point with questions, comments, and bug reports.