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Driven by data or derived through physics? a review of hybrid physics guided machine learning techniques with cyber-physical system (cps) focus
A multitude of cyber-physical system (CPS) applications, including design, control,
diagnosis, prognostics, and a host of other problems, are predicated on the assumption of …
diagnosis, prognostics, and a host of other problems, are predicated on the assumption of …
A review of robot learning for manipulation: Challenges, representations, and algorithms
A key challenge in intelligent robotics is creating robots that are capable of directly
interacting with the world around them to achieve their goals. The last decade has seen …
interacting with the world around them to achieve their goals. The last decade has seen …
Tossingbot: Learning to throw arbitrary objects with residual physics
We investigate whether a robot arm can learn to pick and throw arbitrary rigid objects into
selected boxes quickly and accurately. Throwing has the potential to increase the physical …
selected boxes quickly and accurately. Throwing has the potential to increase the physical …
[HTML][HTML] A survey of robot manipulation in contact
In this survey, we present the current status on robots performing manipulation tasks that
require varying contact with the environment, such that the robot must either implicitly or …
require varying contact with the environment, such that the robot must either implicitly or …
Physgen: Rigid-body physics-grounded image-to-video generation
We present PhysGen, a novel image-to-video generation method that converts a single
image and an input condition (eg., force and torque applied to an object in the image) to …
image and an input condition (eg., force and torque applied to an object in the image) to …
Conceptualizing digital twins
Properly arranging models, data sources, and their relations to engineer digital twins is
challenging. We propose a conceptual modeling framework for digital twins that captures the …
challenging. We propose a conceptual modeling framework for digital twins that captures the …
NeuralSim: Augmenting differentiable simulators with neural networks
Differentiable simulators provide an avenue for closing the sim-to-real gap by enabling the
use of efficient, gradient-based optimization algorithms to find the simulation parameters that …
use of efficient, gradient-based optimization algorithms to find the simulation parameters that …
Residual policy learning
We present Residual Policy Learning (RPL): a simple method for improving
nondifferentiable policies using model-free deep reinforcement learning. RPL thrives in …
nondifferentiable policies using model-free deep reinforcement learning. RPL thrives in …
Incorporating physics into data-driven computer vision
Many computer vision techniques infer properties of our physical world from images.
Although images are formed through the physics of light and mechanics, computer vision …
Although images are formed through the physics of light and mechanics, computer vision …
Modeling of deformable objects for robotic manipulation: A tutorial and review
Manipulation of deformable objects has given rise to an important set of open problems in
the field of robotics. Application areas include robotic surgery, household robotics …
the field of robotics. Application areas include robotic surgery, household robotics …