JetRover ROS robot car with vision arm, powered by Jetson Nano, supporting SLAM mapping and navigation (Standard Kit / Ackerman Chassis / LiDAR A1 / Jetson Nano 4GB)

This link is for JetRover standard kit with Ackerman chassis. Please note that JetRover has 9 versions. For detailed information, please refer to the following instructions.

A professional robot platform for ROS learning and development, supported by NVIDIA Jetson Nano B01 and equipped with a powerful combination of 3D depth cameras and LiDAR.

JetRover includes a 6DOF visual robotic arm with an intelligent serial bus servo device and a torque of 35KG.

The JetRover development kit includes a circular microphone array and speakers, enabling human-machine interaction applications.

Provide multiple control methods, such as WonderAi application (compatible with iOS and Android systems), wireless controller, Robot Operating System (ROS), and keyboard.

! Notes:

JetRover has 9 versions to choose from, please order the corresponding version according to the hardware configuration of the robot.

This product page is the JetRover standard kit with Ackerman chassis version.

1) Ackerman chassis version JetRover development kit:

https://www.robotshop.com/products/hiwonder-jetrover-ros-robot-car-with-vision-robotic-arm-powered-by-jetson-nano-support-slam-mapping-navigation-developer-kit-ackerman-chassis

2) JetRover development kit (with Tank chassis version):

https://www.robotshop.com/products/hiwonder-jetrover-ros-robot-car-with-vision-robotic-arm-powered-by-jetson-nano-support-slam-mapping-navigation-developer-kit-tank-chassis

3) JetRover development kit for Mecanum chassis version:

https://www.robotshop.com/products/hiwonder-jetrover-ros-robot-car-with-vision-robotic-arm-powered-by-jetson-nano-support-slam-mapping-navigation-python

4) JetRover Premium Kit with Mecanum Chassis Version:

https://www.robotshop.com/products/hiwonder-jetrover-ros-robot-car-with-vision-robotic-arm-powered-by-jetson-nano-support-slam-mapping-navigation-advanced-kit-mecanum-chassis-lidar-a1

5) JetRover Advanced Kit with Tank Chassis Version:

https://www.robotshop.com/products/hiwonder-jetrover-ros-robot-car-with-vision-robotic-arm-powered-by-jetson-nano-support-slam-mapping-navigation-advanced-kit-tank-chassis-lidar-a1

6) JetRover standard kit with Mecanum chassis version:

https://www.robotshop.com/products/hiwonder-jetrover-ros-robot-car-with-vision-robotic-arm-powered-by-jetson-nano-support-slam-mapping-navigation-advanced-kit-mecanum-chassis-lidar-a1-1

7) JetRover standard kit with Mecanum chassis version:

https://www.robotshop.com/products/hiwonder-jetrover-ros-robot-car-with-vision-robotic-arm-powered-by-jetson-nano-support-slam-mapping-navigation-advanced-kit-mecanum-chassis-lidar-a1-1

8) JetRover standard kit with tank chassis version:

https://www.robotshop.com/products/hiwonder-jetrover-ros-robot-car-with-vision-robotic-arm-powered-by-jetson-nano-support-slam-mapping-navigation-standard-kit-tank-chassis-lidar-a1

product description

JetRover is a composite ROS robot developed by Hiwonder for ROS education scenarios, supporting three types of motion chassis: Mecanum wheels, Ackermann steering, and crawlers. It is equipped with high-performance hardware configurations such as NVIDIA Jetson Nano, high-performance magnetic encoder motor, 6-degree-of-freedom robotic arm, LiDAR, 3D depth camera, 7-inch LCD screen, far-field microphone array, etc. It can achieve robot motion control, mapping navigation, path planning, obstacle avoidance, autonomous driving, 3D grasping, navigation control, somatosensory interaction, far-field voice interaction, group control formation and other applications.

1) 6-degree-of-freedom robotic arm, intelligent bus servo

JetRover is equipped with a 6DOF robotic arm and a high torque bus high-voltage servo, greatly extending the robot's endurance.

2) LiDAR SLAM surveying and navigation

JetRover is equipped with LiDAR, which can achieve SLAM mapping and navigation, supporting path planning, fixed-point navigation, and dynamic obstacle avoidance.

3) First person perspective of deep vision

JetRover is equipped with a 6-degree-of-freedom robotic arm and a high-performance 3D depth camera at the end, which can achieve target recognition, tracking, and grasping.

4) 6-channel far-field microphone array

The 6CH far-field microphone array and speakers support functions such as sound source localization, voice recognition control, and voice navigation.

1. Support multi chassis expansion

The JetRover composite robot is adaptable to the motion characteristics of various chassis, supporting free switching between Mecanum wheels, Ackermann steering, and tank chassis, and users can adapt according to their own needs.

2. Multiple chassis options for you to choose from

JetRover supports three types of sports chassis structures: Mecanum wheels, Ackermann steering, and tracks. Each chassis has its own unique sports characteristics, and users can choose according to their own needs.

1) Mecanum wheel chassis, 360 ° all-round movement

The Mecanum wheel is a classic omnidirectional wheel that can synthesize torque in any direction by simply adjusting the speed and steering of each wheel, enabling the chassis to move in all directions within a plane.

2) Ackermann chassis, front wheel steering

Ackermann steering is based on the differential angle between the inner and outer wheels. The JetRover robot car adopts a chassis with a 100% Ackermann rate, and the inner wheel rotates more than the outer wheel when turning.

3) Tank chassis differential operation

The tank chassis is easy to operate and has good ground passability, making it widely used in the field of transportation. The JetRover tank chassis consists of nylon tracks, coded motors, drive wheels, load wheels, guide wheels, and support pulleys. The direction of travel and turning angle of the chassis can be freely controlled.

3. Lidar mapping and navigation

JetRover is equipped with LiDAR, which supports path planning, fixed-point navigation, navigation obstacle avoidance, multiple algorithm mapping, and implements LiDAR guarding and LiDAR tracking functions.

1) Various 2D LiDAR surveying methods

JetRover adopts various mapping algorithms such as Gmapping, Hector, Karto, and Cartographer, and supports functions such as path planning, fixed-point navigation, and navigation obstacle avoidance.

2) Fixed-point navigation multi-point navigation

Robots use LiDAR to detect their surrounding environment and support common navigation scenarios for commercial robots, such as fixed-point navigation, multi-point continuous navigation, and multi-point loop navigation.

3) TEB path planning, dynamic obstacle avoidance

Support A * global path planning, TEB/DWA multiple local path planning algorithms, real-time detection of obstacles during navigation, and re planning of path avoidance.

4) RRT independently explores surveying and mapping

Without manual intervention, JetRover utilizes the RRT algorithm to autonomously explore and complete mapping, saving maps, and returning to the starting point.

5) Lidar Guard

Guard the surrounding environment and sound an alarm when an intruder is detected.

6) Lidar tracking

Lidar enables robots to track targets by scanning moving objects ahead.

4. Artificial intelligence autonomous navigation and transportation

JetRover-M1 can use LiDAR for SLAM mapping and navigation in a closed environment, recognize objects through 3D initial vision, grasp objects using inverse kinematics algorithms of robotic arms, and autonomously identify target positions using TEB path planning to complete autonomous navigation and transportation.

1) Map navigation

2) Target capture

3) Path planning

4) Autonomous driving traffic

5. 3D Vision AI upgrade interaction

JetRover is equipped with a large white depth camera, which can effectively perceive environmental changes and achieve intelligent interaction with humans.

1) RTAB-VSLAM 3D Visual Mapping and Navigation

JetRover utilizes the RTAB SLAM algorithm to generate detailed 3D color maps, enabling efficient navigation and obstacle avoidance in complex 3D environments. In addition, JetRover also provides strong support for global positioning within the created maps.

2）ORBSLAM2 + ORBSLAM3

ORB-SLAM is an open-source SLAM framework designed for monocular, binocular, and RGB-D cameras, capable of real-time calculation of camera trajectories and reconstruction of 3D surrounding environments. And in RGB-D mode, the true size of the object can be obtained

3) Depth map data, point cloud

By using the corresponding API JetRover, depth maps, color images, and point clouds of the camera can be obtained.

4) Edge detection

Deep vision allows you to obtain table depth data, enabling you to detect the edges of the table.

5) Crossing a single wooden bridge

Through the 3D depth camera on the robotic arm, the road ahead can be detected and the vehicle's speed can be adjusted to achieve bridge deck driving.

6. Deep learning autonomous driving

In the ROS system, JetRover has deployed the deep learning framework PyTorch, open-source image processing library OpenCV, object detection algorithm YOLOv5, and high-performance inference acceleration engine TensorRT to help users who want to explore the field of autonomous driving technology easily enjoy AI autonomous driving.

1) Road sign detection

By training a deep learning model library, JetRover can achieve autonomous driving functionality with Al vision.

2) Lane keeping

JetRover is able to recognize both lanes and maintain a safe distance from them.

3) Automatic parking

Combining deep learning algorithms to simulate real scenes, lateral parking and parking can be achieved through Ackermann steering.

4) Turn to Decision Making

Based on road signs and traffic signals, JetRover will evaluate traffic conditions and decide whether to turn.

7. AI Visual Interaction

By integrating artificial intelligence, JetRover can achieve KCF target tracking, Al deep learning, color/target recognition and tracking, AR augmented reality, and more.

1) KCF target tracking

By relying on the KCF filtering algorithm, robots can track selected targets.

2) Following the gaze

JetRover supports custom color selection, and the robot car can recognize color lines and follow them.

3) Color recognition and tracking

JetRover can recognize and track specified colors, and can simultaneously recognize multiple April Tags and their coordinates.

4) AR Augmented Reality

Select the corresponding graphics through the app and have them presented on the April Tag code using AR enhancement technology.

5) MediaPipe development, AI interaction upgrade

JetRover can recognize and track specified colors, and can simultaneously recognize multiple April Tags and their coordinates.

6) AI deep learning framework

Utilize YOLO network algorithm and deep learning model library for object recognition.

8. 6CH far-field microphone array function

1) Sound source localization

By using a 6-microphone array to achieve high-precision positioning of noise reduction sources, combined with LiDAR distance recognition, Hiwonder can be summoned from any location.

2) TTS voice broadcast

The text content released by ROS can be directly converted into voice broadcasts for easy interaction design.

3) Voice interaction

Combining speech recognition with TTS voice broadcasting to achieve voice interaction and support the expansion of iFlytek's online voice dialogue function.

4) Voice navigation

Use voice commands to control Hiwonder to reach any designated location on the map, similar to the voice control scenario of a food delivery robot.

9. Interconnected formation

Through multi machine communication and navigation technology.

JetRover can achieve multi aircraft formation performances and artificial intelligence games.

1) Multi car navigation

JetRover relies on multi machine communication to achieve multi vehicle navigation path planning and intelligent obstacle avoidance.

2) Intelligent formation

A batch of jetRovers can maintain a formation including horizontal lines, vertical lines, and triangles during movement.

3) Group control

Only one wireless controller is needed to control a set of JetRovers and execute actions uniformly and synchronously