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Autonomous Vehicle System 2.0


Notchbit AV 2.0 is a real-time end to end camera based full-stack autonomous vehicle driving AI system.

  • Supports RGB and Grayscale fisheye cameras.
  • Operates using at least 2 cameras, up to 4 cameras.
  • 2D Lidar point cloud is optional for higher safety functions.
  • Adopts SIL 3 safety level.
  • Designed for AMR robots at low speed up to 30 Km/h.
  • Operational for indoor or controlled outdoor environments.
  • Operates using pre-installed maps or using online SLAM.
  • Supports multi-destination navigation.
  • Supports OTA, remote diagnostics, and remote control.
  • Supports collision detection with obstacle avoidance.

    Currently supported end user functions

    • Autonomous driving based on single front fisheye camera.
    • Single target navigation with collision detection only.
    • Operates for indoor environment using pre-installed map.

    Product facts

    System requirements

    • RTX 3060 GPU or Orin AGX
    • RAM Footprint: 4 GB
    • ROM Footprint: 1.6 GB
    • CPU load: 60% @ quad-core armv8 @ 1.2 GHz

    Software requirements

    • Linux / QNX
    • PyTorch 2.5 C++ libraries
    • CUDA 12.0

    Notchbit AV 2.0 is provided in several options

    • As a software docker image or virtual machine.
    • As a standalone ECU.

    Product system architecture is based on end to end model

    • System components are trained end-to-end.
    • The system uses the LLM models concepts to generate driving sequence.
    • The system is monitored using a coupled 2D Lidar based system.

    Synthetic training system is based on latest autonomous mobile robot simulators

    • The system is based on Nvidia IssacSim and Cosmos for realistic data generation.
    • Implements Notchbit latest technology reinforcement learning system.
    • Utilizes Notchbit latest training scenarios management system, with CI/CD pipeline support.

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