phyzical

Computer Vision Platforms

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A browser-based embodied data collection platform enables users to teleoperate simulated robotic arms in a 3D web environment without any hardware or specialized expertise, facilitating rapid generation of manipulation demonstration data. Its main features include real-time joint, end-effector, and object pose capture at high frequency, integration with simulation environments using Unity WebGL and Isaac Sim, domain randomization for diverse scene variation, and provenance tracking on a data management system, solving challenges like expensive and slow data collection, limited dataset diversity, and hardware dependency for robotics research, making it suitable for researchers, developers, and AI practitioners working on robot learning, imitation learning, and autonomous manipulation systems.

phyzical can be found in Computer Vision Platforms categories.

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phyzical Main Features

• Task Board
  You can choose tasks like pick-and-place or drawer opening, see how hard they are, and what rewards they offer.
• VLA-Ready Data
  The data is prepared so it can be used for visual language learning and training robots.
• Simulation First
  The SaaS uses simulations to generate and test robot data before use in real life.
• Imitation Learning
  Robots learn by watching demonstrations, similar to how humans learn by example.
• Provenance on Base
  All data shows where it came from, so you know its source and quality.
• Unity WebGL Support
  You can control robots directly in a web browser using Unity WebGL scenes.
• Domain Randomization
  It changes scene details randomly to help robots learn to work in many different environments.
• Fast Data Collection
  The whole process from task selection to data collection takes just minutes.
• No Hardware Required
  You only need a computer and internet connection to contribute or control robots.
• Browser Teleoperation
  You can control robots using just your web browser without any special hardware or skills.
• Isaac Sim Augmentation
  The SaaS uses Isaac Sim to add realistic scenarios and variations to robot data.
• High-Frequency Trajectory Capture
  It records robot movements at 60 times per second to gather detailed data.

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