Neobotics provides an open‑source robotics platform called NeoRacer V1 that lets high schools and colleges teach and experiment with autonomous vehicle technology. The system combines affordable hardware—such as a Jetson Orin Nano, 2D LiDAR, and camera‑ready design—with a Unity‑based simulation environment for reinforcement‑learning training, enabling hands‑on learning in autonomy and machine learning.
Funding
Funding not disclosed
Founders
Product
Problem
High schools and colleges often lack affordable, standardized platforms that allow students to gain practical experience with autonomous vehicle technology and machine learning, limiting hands‑on learning and research opportunities in this emerging field.
Solution
Neobotics offers the NeoRacer V1, an education‑focused autonomous vehicle kit that integrates an NVIDIA Jetson Orin Nano processor, 2D LiDAR, and camera-ready hardware into a compact, pre‑assembled chassis. The platform includes open‑source CAD files, a ROS 2 software stack, and a Unity‑based simulation environment for reinforcement‑learning training, enabling a seamless transition from virtual to physical testing. By providing a complete ecosystem—hardware, software drivers, and documentation—students can develop perception, SLAM, and control algorithms without extensive setup. The system’s affordability and modular design make it suitable for classroom instruction, labs, and student competitions, while the open‑source approach encourages customization and community contributions.
Target Audience
Primary customers are high school and college robotics programs, engineering labs, and educators seeking a turnkey platform for teaching autonomous systems and machine‑learning concepts.
Features
- NVIDIA Jetson Orin Nano (8 GB) with built‑in AI accelerator (67 TOPS) for on‑board inference
- Industrial‑grade 2D LiDAR (30 Hz, 25 m range) and 1080p 120 FPS camera for perception and SLAM
- ROS 2 driver and software stack (NeoRacer Backend) enabling modular node‑based development
- Unity‑based high‑fidelity simulation environment supporting reinforcement‑learning training
- Open‑source chassis design with CAD files and manufacturing documentation
- Pre‑assembled kit with independent suspension, Ackermann steering, and 4WD drivetrain
- Comprehensive documentation guiding users from initial setup to autonomous racing