Visual Asset Management System (VAMS) is a purpose-built, AWS native solution for the management and distribution of traditional to specialized visual assets used in physical AI and spatial computing.

EmbodiedAgents is a fully-loaded ROS2 based framework for creating interactive physical agents that can understand, remember, and act upon contextual information from their environment.

PAI-Bench: A Comprehensive Benchmark for Physical AI

Agentic AI Robot: Industrial Safety Monitoring and Control

An evolving, end-to-end reference for collecting and augmenting data, training, evaluating, and deploying embodied AI systems. Accelerate physical AI with cloud-first pipelines, reproducible workflows, and clear paths from research to production.

This screenshot illustrates the installation process for setting up Lang2Pose. Follow these steps to ensure your environment is correctly configured before running the system.

An world first open standardized protocol enabling communication for autonomous robots to exchange data, coordinate tasks, and collaborate in real-time environments in the age of AI.

a useful tool can convert data between hdf5 and mcap

書籍『システム制御理論と統計的機械学習』のサポートページです。

Complete Physical AI & Humanoid Robotics textbook with 87 interactive lessons, AI chatbot, ROS 2, NVIDIA Isaac Sim, and hands-on projects. Built with Docusaurus.

Investigating AI fairness vulnerabilities in RL-driven RIS for B5G/6G networks. Research toolkit for bias analysis, mitigation strategies, and robust wireless communication systems.

A lightweight Python SDK that turns raw videos into segmentation-ready datasets using ffmpeg, SAM-3, and pluggable backends.

AI-native textbook for Physical AI & Humanoid Robotics built with Docusaurus, FastAPI, and RAG-powered chatbot. Features content personalization and Urdu translation.

Scalable Training Telemetry and Metrics Visualization