Per-Contact Iteration Method for Solving Contact Dynamics
By Jemin Hwangbo, Marco Hutter. 2018
263 citations recorded by the source corpus.
Subfields: Biomedical Engineering, Control and Systems Engineering, Mechanics of Materials
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
- Marco Hutter
- Jitendra Malik
- Jemin Hwangbo
- Deepak Pathak
- Ashish Kumar
- Vladlen Koltun
- Lorenz Wellhausen
- Zipeng Fu
In Control and Systems Engineering
- Marco Hutter
- Jemin Hwangbo
- Vladlen Koltun
- Jitendra Malik
- Deepak Pathak
- Lorenz Wellhausen
- Ashish Kumar
- Zipeng Fu
In Mechanics of Materials
- Vladlen Koltun
- Jitendra Malik
- Ashish Kumar
- Deepak Pathak
- Zipeng Fu
- Lorenz Wellhausen
- Marco Hutter
- Jemin Hwangbo
Citations in the corpus
- Learning agile and dynamic motor skills for legged robots (2019, methodology): “rs (as provided in [22, 54]) for all learning sessions presented in this paper. We used a fast custom implementation of the algorithm [55]. This efficient implementation and fast rigid-body simulation [41] allowed us to generate and process about a quarter of a billion state transitions in roughly fo”
- RMA: Rapid Motor Adaptation for Legged Robots (2021, methodology): “Simulation Setup: We use the RaiSim simulator [21] for rigid-body and contact dynamics simulation.”
- Learning robust perceptive locomotion for quadrupedal robots in the wild (2022, methodology): “We use RaiSim [58] as our simulator to build the training environment.”
- Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learning (2021, unknown): “Common robotic simulators such as Mujoco [5], Bullet [6], or Raisim [7] feature efficient multi-body dynamics implementations.”