From 2a2467098108641483778c09ceb7906cb49f6cee Mon Sep 17 00:00:00 2001 From: Geonhee-LEE Date: Sat, 21 Aug 2021 21:55:30 +0900 Subject: [PATCH] correct typos --- README.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index e86982b..499a8e2 100644 --- a/README.md +++ b/README.md @@ -17,8 +17,8 @@ Due to use only basic libralies (scipy, numpy), this library is easy to extend f |:----------|:---------------: |:----------------:|:----------------:|:----------------:|:----------------:| | Linear Model Predictive Control (MPC) | ✓ | x | x | x | x | | Cross Entropy Method (CEM) | ✓ | ✓ | x | x | x | -| Model Preidictive Path Integral Control of Nagabandi, A. (MPPI) | ✓ | ✓ | x | x | x | -| Model Preidictive Path Integral Control of Williams, G. (MPPIWilliams) | ✓ | ✓ | x | x | x | +| Model Predictive Path Integral Control of Nagabandi, A. (MPPI) | ✓ | ✓ | x | x | x | +| Model Predictive Path Integral Control of Williams, G. (MPPIWilliams) | ✓ | ✓ | x | x | x | | Random Shooting Method (Random) | ✓ | ✓ | x | x | x | | Iterative LQR (iLQR) | x | ✓ | x | ✓ | x | | Differential Dynamic Programming (DDP) | x | ✓ | x | ✓ | ✓ | @@ -36,10 +36,10 @@ Following algorithms are implemented in PythonLinearNonlinearControl - [Cross Entropy Method (CEM)](https://arxiv.org/abs/1805.12114) - Ref: Chua, K., Calandra, R., McAllister, R., & Levine, S. (2018). Deep reinforcement learning in a handful of trials using probabilistic dynamics models. In Advances in Neural Information Processing Systems (pp. 4754-4765) - [script](PythonLinearNonlinearControl/controllers/cem.py) -- [Model Preidictive Path Integral Control of Nagabandi, A. (MPPI)](https://arxiv.org/abs/1909.11652) +- [Model Predictive Path Integral Control of Nagabandi, A. (MPPI)](https://arxiv.org/abs/1909.11652) - Ref: Nagabandi, A., Konoglie, K., Levine, S., & Kumar, V. (2019). Deep Dynamics Models for Learning Dexterous Manipulation. arXiv preprint arXiv:1909.11652. - [script](PythonLinearNonlinearControl/controllers/mppi.py) -- [Model Preidictive Path Integral Control of Williams, G. (MPPIWilliams)](https://ieeexplore.ieee.org/abstract/document/7989202) +- [Model Predictive Path Integral Control of Williams, G. (MPPIWilliams)](https://ieeexplore.ieee.org/abstract/document/7989202) - Ref: Williams, G., Wagener, N., Goldfain, B., Drews, P., Rehg, J. M., Boots, B., & Theodorou, E. A. (2017, May). Information theoretic MPC for model-based reinforcement learning. In 2017 IEEE International Conference on Robotics and Automation (ICRA) (pp. 1714-1721). IEEE. - [script](PythonLinearNonlinearControl/controllers/mppi_williams.py) - [Random Shooting Method (Random)](https://arxiv.org/abs/1805.12114)