The Lifelong Learning team is closing in on the SysID-Control-Simulation problem.
Research into the literature for control theory and system identification included Linearly Weighted Projection Regression, Sparse Online Gaussian Processes, derivatives of Partial Least Squares such as Direct Kernel PLS, and ILQG again. For our planned experiment with fault tolerant control, it is extremely important that the learning be incremental and converge quickly to a model usable to by a controller, so LWPR and SOGP were of interest. However, these more complicated algorithms ought to have been reserved until things such as regression on the system with the state variables + control signal + kernel trick + trigonometric functions was implemented as a basic test (completed at beginning of Week 6). Swing-up of a single-actuated double pendulum through ILQG was completed at the end of Week 5.
Going into Week 6, the integration of the three subtasks needs to be completed as soon as possible. Hopefully, through collaboration with other labs, any issues with ROS and Gazebo can be resolved.
The planned experiment is expected to be highly informative, and demonstrate the failure points of our approach. We should then be able to plan or at least sketch out 2-3 subprojects for the remainder of the summer to attempt the integration of Lifelong Learning and Fault-Tolerant Control.