Categories: AI/ML News

A scalable reinforcement learning–based framework to facilitate the teleoperation of humanoid robots

The effective operation of robots from a distance, also known as teleoperation, could allow humans to complete a vast range of manual tasks remotely, including risky and complex procedures. Yet teleoperation could also be used to compile datasets of human motions, which could help to train humanoid robots on new tasks.

Interactive Fleet Learning

April 7, 2023

In "AI/ML Research"

ARMADA: Augmented Reality for Robot Manipulation and Robot-Free Data Acquisition

Teleoperation for robot imitation learning is bottlenecked by hardware availability. Can high-quality robot data be collected without a physical robot? We present a system for augmenting Apple Vision Pro with real-time virtual robot feedback. By providing users with an intuitive understanding of how their actions translate to robot motions, we…

December 18, 2024

In "FAANG"

Humanoid robots can swiftly get up after they fall with new learning framework

Humanoid robots, which have a body structure that mirrors that of humans, could rapidly and effectively tackle a wide range of tasks in real-world settings. These robots and their underlying control algorithms have improved considerably in recent years. Many of them can now move faster, emulating various human-like movements.

February 25, 2025

In "AI/ML News"

AI Generated Robotic Content