Simulation-based design of dynamic controllers for humanoid balancing
By Jie Tan, Zhaoming Xie, Byron Boots, Karen Liu. 2016
56 citations recorded by the source corpus.
Subfields: Biomedical Engineering, Computer Vision and Pattern Recognition, Control and Systems Engineering
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Biomedical Engineering
- Sergey Levine
- Jie Tan
- Xue Bin Peng
- Dieter Fox
- Yevgen Chebotar
- Tingnan Zhang
- Danijar Hafner
- Yunfei Bai
In Computer Vision and Pattern Recognition
- Sergey Levine
- Jitendra Malik
- Luc Van Gool
- Dacheng Tao
- Trevor Darrell
- Li Fei-Fei
- Xiaogang Wang
- Ming-Hsuan Yang
In Control and Systems Engineering
- Sergey Levine
- Chelsea Finn
- Pieter Abbeel
- Jie Tan
- Dieter Fox
- Yevgen Chebotar
- Danijar Hafner
- Xue Bin Peng
Citations in the corpus
- Closing the Sim-to-Real Loop: Adapting Simulation Randomization with Real World Experience (2018, methodology): “In [30], an iterative system identification framework is used to optimize trajectories of a bipedal robot in simulation and calibrate the simulation parameters by minimizing the discrepancy between”
- Sim-to-Real: Learning Agile Locomotion For Quadruped Robots (2018, background): “[45] found the optimal physical parameters that should be used in simulation for a particular task.”
- Learning Agile Robotic Locomotion Skills by Imitating Animals (2020, background): “Sim-toreal transfer can be facilitated by constructing more accurate simulations [58, 62], or adapting the simulator with realworld data [57, 23, 26, 36, 5].”
- Fast Model Identification via Physics Engines for Data-Efficient Policy Search (2017, methodology): “VGMI is compared against a) Covariance Matrix Adaptation Evo-Proceedings lution Strategy (CMA-ES) [ Tan et al. , 2016 ] The number of iterations for policy search varies on problem difficulty.”