Yahboom AI ROS Robot Car Kit Autonomous Driving Training Ackerman Structure Python Programming (R2L Standard Edition with Jetson Nano 4GB SUB Board)

ROS Robot Operating System.

Al deep learning framework.

Python programming and OpenCV image processing.

Visual tracking and autonomous driving.

Cross platform interconnection control.

ROSMASTER R2L is a robot with Ackermann steering structure, designed specifically for autonomous driving, supporting Jetson NANO, developed based on ROS and Ubuntu operating system. We use a 2MP high-definition camera combined with some recognition algorithms to achieve functions such as model training, autonomous driving, object recognition, and tag tracking. Like other Yahboom robot cars, R2L supports APP/joystick expression control. We offer 80 courses with Chinese and English subtitles to help users quickly get started with model training for autonomous driving and the ROS operating system.

1. Complete R2L robot code programming based on Robot Operating System (ROS) and showcase the latest autonomous driving and artificial intelligence recognition technologies.

2. The control board can be Jetson Nano. The robot must be controlled with a development board, otherwise it cannot be started.

The R2L robot adopts the Ackermann chassis structure design, which utilizes structural advantages to reduce power consumption while making the car's steering more stable, fast, and precise, thereby improving competition efficiency. This is a cool thing in model game competitions.

4. Can be used with Yahboom autopilot track (3.2 x 2.8m): https://www.robotshop.com/products/yahboom-r2

Inventory model: RM-YAHB-03H

The R2L robot kit has trained a model for this map and can be driven directly.

5. Multiple control modes: This robot kit is equipped with a remote control handle and user interface, which can be accessed through mobile devices or PCs. Enjoy the fun of handling to the fullest.

☆★★☆ Very important:

How to choose Yahboom ROSMASTER R2 or R2L robot?

▶ The R2 robot is equipped with a depth camera, LiDAR, and voice interaction module to meet the needs of mapping navigation, deep learning, 3D vision/speech recognition, robot formation, and more.

▶ The R2L robot is equipped with a high frame rate wide-angle camera and can be optionally equipped with an automatic track. It uses Jetson series board GPUs for model training and camera visual recognition, completing the recognition of traffic signs and traffic lights, as well as track autonomous driving.

♦ The similarities between R2 and R2L robots include Ackermann steering structure, ROS robot operating system, OpenCV visual recognition, APP remote control, and FPV handle remote control.

♦ The difference is that the R2 robot supports functions such as depth camera 3D scanning, LiDAR mapping and navigation, robot voice interaction control, and multi robot formation interconnection control, while the R2L robot focuses on model training and autonomous driving.