Ai in robotics - Labellerr AI

Ai in robotics

A collection of 10 posts

data annotation

ROBOTURK Explained: A Scalable Path to Training Smarter Robots

ROBOTURK solves the core bottleneck in robot learning by enabling large-scale, high-quality demonstrations through smartphones and cloud simulation. It offers a scalable way to teach robots complex manipulation skills without expensive lab hardware.

From ImageNet to BEHAVIOR-1K and the evolution of structured data in AI

From ImageNet to BEHAVIOR-1K and the evolution of structured data in AI

Introduction Over the past decade, some of the biggest leaps in artificial intelligence have been driven not just by better algorithms, but by better data. When Fei-Fei Li introduced the ImageNet dataset in 2009, it gave researchers a common foundation of structured training data that unlocked new levels of performance

NVIDIA Isaac GR00T N1

NVIDIA Isaac GR00T N1 Foundation Model For Humanoid Robots

Isaac GR00T N1—from NVIDIA—is an open foundation model and simulation toolkit enabling powerful reasoning, multistep manipulation, and cross-embodiment skills for humanoid robots. Modular, simulation-powered, and scalable for rapid AI robot development

Scaling Surgical Data Annotation Workflows

Scaling Surgical AI Data Annotation Workflows

Explore how to efficiently scale surgical data annotation workflows in medical imaging and video analysis. This guide covers best practices, tools, and strategies to enhance AI model performance and streamline the annotation process.

Data Annotation In Robotics

How Data Annotation Is Powering The Humanoid Robots

Data annotation is the foundation of robotics AI. From 3D labeling to semantic segmentation, it powers perception, navigation, and manipulation, helping robots see, understand, and interact with the world precisely and safely.

Data Labeling for Humanoid Robotics

Data Labeling for Humanoid Robots

Humanoid robots rely on precise data labeling to understand and interact with their environment. Accurate annotations in vision, speech, and sensor data enhance their ability to navigate, recognize objects, and communicate effectively. Discover how data labeling powers AI-driven humanoid robotics.

Why Robots Are Finally Learning to Think, See, and Act Like Humans?

VisionLanguageActionModels

How Vision-Language-Action Models Powering Humanoid Robots

Vision-Language-Action (VLA) models are transforming robotics by integrating visual perception, natural language understanding, and real-world actions. This groundbreaking AI approach enables robots to comprehend and interact with their environment like never before.

Influence of robotics in 2025 - challenges, usage by different industries, market trends, key driving factors.

Building Smarter Robotic Arms in 2025

Discover how Tau Robotics is revolutionizing the robotics industry in 2025 with cutting-edge AI-powered robotic arms. From healthcare to manufacturing, explore their innovative solutions driving smarter automation and shaping the future of robotics.

Evolving industries with data labeling who benefits the most?

What Industries Benefit Most from Data Labeling?

Discover which industries benefit most from data labeling, including healthcare, retail, automotive, and finance. How it enhances AI applications, improving tasks like image recognition, sentiment analysis, and autonomous driving, leading to more accurate and efficient outcomes in these sectors.

Top Data Annotation and Labeling Tools for Robotics and Manufacturing

7 Best Data Annotation and Labeling Tools in Robotics and Manufacturing Industry

In the rapidly evolving fields of robotics and manufacturing, the integration of machine learning and artificial intelligence has become indispensable. These technologies rely heavily on vast amounts of high-quality data to train algorithms and improve performance. Central to this process is data labelling and annotation, a critical step that involves