If a model or policy is mainly trained in a simulator but expected to work on a real robot, it would surely face the sim2real gap. Domain Randomization (DR) ...
If a model or policy is mainly trained in a simulator but expected to work on a real robot, it would surely face the sim2real gap. Domain Randomization (DR) ...
We've trained a human-like robot hand to manipulate physical objects with unprecedented dexterity.
Given that policy search corresponds to this more difficult context, we consider five solutions: 1. searching for high utility policy parameters without building a utility model (Section ...
Donkey Car trained with Double Deep Q Learning (DDQN) in Unity Simulator.
By adding randomness to a relatively simple simulation, OpenAI's robot hand learned to perform complex in-hand manipulation
This week, NVIDIA researchers from the newly opened robotics research lab in Seattle, Washington are presenting a new proof of concept reinforcement learning approach that aims to enhance ...
Grasping real-world objects is considered one of the more iconic examples of the current limits of machine intelligence. While humans can easily grasp and pick up objects they’ve never seen ...
In the last years, artificial neural networks (ANN) have successfully been applied across a number of tasks. However, designing well performing ANNs requires expert knowledge and ...
I read an article entitled Games Hold the Key to Teaching Artificial Intelligent Systems, by Danny Vena, in which the author states that computer games like Minecraft, Civilization, and ...
Computers are illiterate. Reading requires mapping the words on a page to shared concepts in our culture and commonsense understanding, and…
Turns out replacing humans isn't that easy after all
New approach aims to enhance how robots trained in simulation will perform in the real world.
Simulation-Based Design of Dynamic Controllers for Humanoid Balancing Jie Tan Zhaoming Xie Byron Boots C. Karen Liu Abstract— Model-based trajectory optimization often fails to find a ...
Bayesian deep learning methods often look like a theoretical curiosity, rather than a practically useful tool, and I'm personally a bit skeptical about the practical usefulness of some of ...