Mar 20, 2019 · Abstract:We present a method for fast and accurate physics-based predictions during non-prehensile manipulation planning and control.

Feb 17, 2022 · We present a method for fast and accurate physics-based predictions during non-prehensile manipulation planning and control.

By combining the two physics models, the Parareal algorithm is used to combine a coarse pushing model with an off-the-shelf physics engine to deliver ...

We use Parareal to combine a coarse pushing model with an off-the-shelf physics engine to deliver physics-based predictions that are as accurate as the physics ...

We use Parareal to combine a coarse pushing model with an off-the-shelf physics engine to deliver physics-based predictions that are as accurate as the physics ...

We adapt Parareal to combine a coarse pushing model with an off-the-shelf physics engine to deliver physics-based predictions that are as accurate as the ...

Aug 30, 2019 · We propose combining a coarse (i.e. computationally cheap but not very accurate) predictive physics model, with a fine (i.e. computationally ...

Combining Coarse and Fine Physics for Manipulation using Parallel-in-Time Integration (2019). First Author: Agboh, W. Attributed to: Humanlike physics ...

Combining Coarse and Fine Physics for Manipulation using Parallel-in-Time Integration. WC Agboh, D Ruprecht, MR Dogar. International Symposium on Robotics ...

Parallel-in-time integration methods such as Parareal can help to leverage parallel computing to accelerate physics predictions and thus planning. The Parareal ...