- Powered by NVIDIA Jetson Nano and based on ROS
- Support Lidar for mapping and navigation
- Optional depth camera for 3D vision mapping and navigation/ Optional 7-inch touch screen for parameter monitoring and debugging
- Optional 6-microphone array for voice interaction
- Three versions are available. JetAuto Starter Kit (with Lidar), jetAuto Standard Kit (with Lidar and Depth Camera), JetAuto Advanced Kit (with Lidar, Depth Camera, LCD Screen and 6-microphone Array)
Tutorial Link for JetAuto: https://drive.google.com/drive/folders/16pwHYO8rK-22oAzStc7-olP9Weq7AbzY?usp=sharing
This version is JetAuto Starter Kit.
For JetAuto Standard Kit (with Lidar and Depth Camera), please go to: https://www.robotshop.com/en/hiwonder-jetauto-ros-robot-car-powered-by-jetson-nano-with-lidar-depth-camera-standard-kit.html
For JetAuto Advanced Kit (with Lidar, Depth Camera, LCD Screen and 6-microphone Array), please go to: https://www.robotshop.com/en/hiwonder-jetauto-ros-robot-car-powered-by-jetson-nano-with-lidar-depth-camera-screen-advanced-kit.html
JetAuto is an entry-level ROS robot car tailored for ROS education. It is loaded with NVIDIA Jetson Nano, high-performance encoder motor, rotatable pan-tilt, Lidar, 3D depth camera and 7-inch screen, which opens up more functionalities. Robot motion control, mapping and navigation, path planning, tracking and obstacle avoidance, autonomous driving, human feature recognition, somatosensory interaction and voice interaction all can be achieved!
Diverse combination of the hardware makes JetAuto an ideal platform where you can learn and verify robotic SLAM function, as well as get the solution to ROS development. Massive ROS learning materials and tutorials are provided to help you get started quickly!
Jetson Nano Control System:
NVIDIA Jetson Nano is able to run mainstream deep learning frameworks, such as TensorFlow, PyTorch, Caffe/ Caffe2, Keras, MXNet. Provide powerful computing power for massive AI projects. Powered by Jetson Nano, JetAuto can implement image recognition, object detection and positioning, pose estimation, semantics segmentation, intelligent analysis and other almighty functions.
2D Lidar Mapping and Navigation——JetAuto is loaded with high-performance Lidar that supports mapping with diverse algorithms including Gmapping, Hector, Karto and Cartographer. In addition, path planning, fixed-point navigation as well as obstacle avoidance amid navigation can be implemented.
Single-point Navigation, Multi-point Navigation——JetAuto employs Lidar to detect the surroundings in real time to achieve single-point navigation as well as multi-point navigation.
TEB Path Planning, Obstacle Avoidance——It supports TEB path planning, and is able to monitor the obstacle in real time during navigation. Therefore, it can replan the route to avoid the obstacle and continue moving.
RRT Autonomous Exploration Mapping——Adopting RRT algorithm, JetAuto can complete exploration mapping, save the map and drive back to the starting point autonomously, so there is no need for manual control.
Lidar Tracking——By scanning the front moving object, Lidar makes robot capable of target tracking.
Lidar Guarding——Guard the surroundings and ring the alarm when detecting intruder.
RTAB-VSLAM 3D Mapping and Navigation——Depth camera supports 3D mapping in two ways, pure RTAB vision and fusion of vision and Lidar, which allows JetAuto to navigate and avoid obstacle in 3D map, as well as re-locate globally.
ORBSLAM2 + ORBSLAM3——ORB-SLAM is an open-source SLAM framework for monocular, binocular and RGB-D cameras, which is able to compute the camera trajectory in real time and reconstruct 3D surroundings. And under RGB-D mode, the real dimension of the object can be acquired.
Depth Map Data, Point Cloud——Through the corresponding API, JetAuto can get depth map, color image and point cloud of the camera.
Deep Learning, Autonomous Driving：
With JetAuto, you can design an autonomous driving scenario to put ROS into practice, which enables you to better understand core functions of autonomous driving.
Road Sign Detection——Through training the deep learning model library, JetAuto can realize autonomous driving with AI vision.
Lane Keeping——JetAuto is capable of recognizing the lanes on both sides to maintain safe distance between it and the lanes.
Automatic Parking——Combined with deep learning algorithm, JetAuto can recognize the parking sign, then steers itself into the slot automatically.
Turning Decision Making——According to the lanes, road signs and traffic lights, JetAuto will estimate the traffic and decide whether to turn.
MediaPipe Development, Upgraded AI Interaction：
Based on MediaPipe framework, JetAuto can carry out human body recognition, fingertip detection, face detection, 3D detection and more.
1) Fingertip Trajectory Recognition
2) Human Body Recognition
3) 3D Detection
4)3D Face Detection
AI Deep Learning Framework—— Utilize YOLO network algorithm and deep learning model library to recognize the objects.
KCF Target Tracking——Relying on KCF filtering algorithm, the robot can track the selected target.
Color/Tag Recognition and Tracking——JetAuto is able to recognize and track the designated color, and can recognize multiple April Tags and their coordinates.
Augmented Reality (AR)——After you select the patterns on the APP, the patterns can be overlaid on the April Tag.
Far-field Microphone Array:
This 6-microphone array is adroit at far-field sound source localization, voice recognition and voice interaction. In comparison to ordinary microphone module, it can implement more advanced functions.
1) Sound Source Localization
2) Voice Interaction
3) Voice Navigation
Depending on multi-machine communication, JetAuto can achieve multi-vehicle navigation, path planning and smart obstacle avoidance.
Intelligent Formation——A batch of JetAuto cars can maintain the formation, including horizontal line, vertical line and triangle, during moving.
Group Control——A group of JetAuto can be controlled by only one wireless handle to perform actions uniformly and simultaneously.
ROS Robot Operating System：
ROS is an open-source meta operating system for robots. It provides some basic services, such as hardware abstraction, low-level device control, implementation of commonly used functionality, message-passing between processes, and package management. And it also offers the tools and library functions needed to obtain, compile, write, and run code across computers. It aims at providing code reuse support for robotics research and development.
JetAuto employs ROS framework and supports Gazebo simulation. Gazebo brings a fresh approach for you to control JetAuto and verify the algorithm in simulated environment, which reduces experimental requirements and improves efficiency.
JetAuto Simulation Control——The kinematics algorithm can be verified in simulation to speed up algorithm iteration and reduce the experiment cost.
Visual Data——rviz can visualize the mapping and navigation result, which facilitates debugging and improving algorithm.
Various Control Methods：
1) WonderAi APP 2) Map Nav APP (Android Only) 3) Wireless Handle
JetAuto (with Lidar) *1
12.6V 2A Charger *1
Card Reader *1
PS2 Wireless Handle *1
This Link is for JetAuto Standard Kit with Lidar and Depth Camera: https://www.robotshop.com/en/hiwonder-jetauto-ros-robot-car-powered-by-jetson-nano-with-lidar-depth-camera-standard-kit.html
This Link is for JetAuto Advanced Kit with Lidar, Depth Camera, LCD Screen and 6-microphone Array: https://www.robotshop.com/en/hiwonder-jetauto-ros-robot-car-powered-by-jetson-nano-with-lidar-depth-camera-screen-advanced-kit.html
1) JetAuto Robot Car:
Material: Full-matal hard aluminum alloy bracket(anodized)
Battery: 11.1V 6000mAh Lipo battery
Continuous working life: 60min
Hardware: ROS controller and ROS expansion board
Operating system: Ubuntu 18.04 LTS + ROS Melodic
Software: iOS/Android APP
Storage: 32GB TF card
Servo: HTS-20H serial bus servo
Control method: phone/handle control
Package size (advanced kit): 335*320*225mm
Package weight (advanced kit): about 4.5kg
2) Hall Encoder Geared Motor:
Rated voltage: 12V
Rated power consumption: 2.4W
Motor type: permanent-magnet brush
Stall current: 3A
Stall torque: 15kgf.cm
Rated current: 0.2A
Rated torque: 10kgf.cm
Reduction ratio: 1 : 90
Rotation speed (before reduction)
Rotation speed (after reduction): 110± 10rpm
Output shaft: D-type eccentric shaft of 6 mm diameter
Encoder type: Hall encoder
Interface: PH2.0 - 6P
Power supply: 3.3 - 5V
3) Lipo Battery:
Plug: DC 5.5 * 2.5 female/ SM-2P male
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