Hiwonder JetAuto ROS Robot Car Powered by Jetson Nano with Lidar Depth Camera Touch Screen(Standard Kit)

• Powered by NVIDIA Jetson Nano(included) and based on ROS
• FPV robotic arm for picking, sorting and transporting
• Depth camera and Lidar for mapping and navigation
• 7-inch touch screen to monitor and debug parameters
• Open-source, ample PDF materials and tutorials are provided

Note:

Tutorial link for JetAuto: https://drive.google.com/drive/folders/16pwHYO8rK-22oAzStc7-olP9Weq7AbzY?usp=sharing

The 6-microphone array for voice interaction are only included in the advanced kit, so if you want to get JetAuto Pro Advanced Kit, please check this link: https://www.robotshop.com/en/jetauto-pro-ros-robot-car-with-vision-robotic-arm-powered-by-jetson-nano-support-slam-mapping-navigation-python-advanced-kit.html

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JetAuto Pro is a comprehensive 2 in 1 ROS robot tailored for ROS learning. It is loaded with NVIDIA Jetson Nano, AI vision robotic arm, high-performance encoder motor, Lidar, 3D depth camera and 7-inch screen, which open up more functionalities. Robot motion control, mapping and navigation, path planning, tracking and obstacle avoidance, autonomous driving, intelligent picking, Movelt simulation, somatosensory interaction and voice interaction all can be achieved!

Diverse combination of the hardware makes JetAuto Pro 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!

Free Changeable Models:

Vision robotic arm and depth camera on JetAuto Pro can be disassembled enabling it to freely switch between two models.

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Lidar Function:

1) 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.

2) 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.

3) 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.

4) 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.

5) Lidar Tracking —— By scanning the front moving object, Lidar makes robot capable of target tracking.

6) Lidar Guarding—— Guard the surroundings and ring the alarm when detecting intruder.

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Depth Camera:

1) 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 Pro to navigate and avoid obstacle in 3D map, as well as relocate globally.

2) 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.

3) Depth Map Data, Point Cloud —— Through the corresponding API, JetAuto Pro can get depth map, color image and point cloud of the camera.

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MediaPipe Development, Upgraded AI Interaction

Based on MediaPipe framework, JetAuto Pro 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

⑤ AI Deep Learning Framework——Utilize YOLO network algorithm and deep learning model library to recognize the objects.

⑥ KCF Target Tracking—— Relying on KCF filtering algorithm, the robot can track the selected target.

⑦ Color/Tag Recognition and Tracking —— JetAuto Pro is able to recognize and track the designated color, and can recognize multiple April Tags and their coordinates at the same time.

⑧ Augmented Reality (AR) —— After you select the patterns on the APP, the patterns can be overlaid on the April Tag.

⑨ ROS robot APP Mapping —— Use APP to control JetAuto Pro to map and navigate, and view images.

⑩ Body Motion Control—— Recognize and analyze your limb and body frame with depth camera first, then perform corresponding action based on your posture.

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Smart Vision Robotic Arm：

Loaded with 5DOF vision robotic arm, JetAuto Pro can pick and sort stuffs. Furthermore, the combination of Lidar and Robotic arm allows JetAuto Pro to transport smartly during navigation.

① Multi-point Navigation Transport； ② URDF Kinematic Simulation Model； ③ Movelt Simulation and Trajectory；Control； ④ Gesture Recognition；⑤ Color Sorting；⑥ Follow Line to Clear Obstacles；⑦ Waste Sorting

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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 Voice Control Navigation； ② Sound Source Localization； ③ Voice Control Robotic Arm；④ Voice Control Color Recognition

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Interconnected Motorcade:

1) Multi-vehicle Navigation—— Depending on multi-machine communication, JetAuto Pro can achieve multi-vehicle navigation, path planning and smart obstacle avoidance.

2) Intelligent Formation—— A batch of JetAuto Pro cars can maintain the formation, including horizontal line, vertical line and triangle, during moving.

3) Group Control —— A group of JetAuto Pro can be controlled by only one wireless handle to perform actions uniformly and simultaneously.

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Gazebo Simulation：

JetAuto Pro employs ROS framework and supports Gazebo simulation. Gazebo brings a fresh approach for you to control JetAuto Pro and verify the algorithm in simulated environment, which reduces experimental requirements and improves efficiency.

1) JetAuto Pro Simulation Control —— The kinematics algorithm can be verified in simulation to speed up algorithm iteration and reduce the experiment cost.

2) Visual Data —— RViz can visualize the mapping and navigation result, which facilitates debugging and improving algorithm.

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Various Control Methods：

① WonderAi APP ② Map Nav APP (Android Only) ③ Wireless Handle