v0.1: WAFR 2018 Release
holds the code for "A Performance Analysis of Differential Dynamic Programming on a GPU."
v0.2: ICRA 2019 Release extends the previous work by integrating LCM for hardware experiments and cleaning up the code base / interface. An extended abstract describing the hardware experiments can be found here.
config.hdefines all of the default settings (parallel level, plant, etc.) for an experiment and imports all of the various helper functions and files from the following folders as needed/examples/*holds the scripts that run the WAFR examples and LCM examples (see the comment at the top of each file for the compilation instructions)/plants/*holds custom rigid body dynamics and/or analytical dynamics and cost functions for currently supported plants/DDPHelpers/*holds most of the functions for DDP as inlined templated CUDA header files/utils/*holds a variety of support code for matrix multiplication, discrete time integrators, thread/CUDA support, etc./test/*holds a variety of testing scripts for various function calls and derivatives (see the comment at the top of each file for the compilation instructions)/lcmtypes/*holds LCM types for multi-computer / hardware communication
- CUDA needs to be installed as code needs to be compiled with the NVCC comiler. Currently, this code has been tested with CUDA 9 and X.
- For multi-computer / hardware MPC code there is an additional communicaiton dependency: LCM.
https://askubuntu.com/questions/1077061/how-do-i-install-nvidia-and-cuda-drivers-into-ubuntu https://www.tensorflow.org/install/gpu
- Install this fork of drake: https://github.com/plancherb1/drake
- You need to put in you .bashrc
export DRAKE_PATH_ROOT=<path_to_drake>Then the scripts in the utils folder should launch the drake visualizer and simulator
- On roadmap to develop a CPU/GPU hybrid (only the gradients on the GPU) and a fully serial CPU version without any instruction level parallelism
- GPU RBDYN for Kuka only works in Euler mode -- need to introduce loops and reduce shared memory for Midpoint and RK3 (or use a brand new GPU which has double the shared memory) -- potential to also optimize the gradient calc to require less shared memory
- CPU MPC suffers from resource contention when trajRunner and Goal are on same computer -- need to improve and provide seperate compile paths -- also CPU MPC Parallel Line Search has a subtle bug (in iLQR is identical to serial but diverges in MPC -- need to debug)
- Constraint handling / penalities need further development - would like to add full AL constraints and/or projection methods
- Final cost shift is in development and non-functional (tied to frequency and not last goal change / shift count)
- SLQ implementation is currently broken (and EE version needs a cost kernel)
- EEVel rpy derivatives are currently broken (may explore forced finite diff)
- BFGS iters may improve / stabilize the EEPos/Vel cost and should be explored
- Square root implementation of DDP should add numerical stability and should be explored
- Want to develop URDF > transforms and inertias tool for Arm
- Would be nice to add a runtime and not compile time switch for Hardware vs. Sim mode and for level of parallelism