- Powered by NVIDIA Jetson Nano (included) and based on ROS
- Support depth camera (optional) and Lidar (included) for mapping and navigation
- Optional 7-inch touch screen for parameter monitoring and debugging
- Optional 6-microphone array for voice interaction
- Open-source, and ample PDF materials and tutorials are provided
Reminder:
This version is JetAuto Starter Kit (only Lidar included)
For JetTank Standard Kit (with Lidar and Depth Camera), please go to: https://www.robotshop.com/products/hiwonder-jettank-ros-robot-tank-powered-by-jetson-nano-with-lidar-depth-camera-touch-screen-support-slam-mapping-navigation-standard-kit
For JetTank Advanced Kit (with Lidar, Depth Camera, 7-ich LCD Screen and 6-microphone Array), please go to: https://www.robotshop.com/products/hiwonder-jettank-ros-robot-tank-powered-by-jetson-nano-with-lidar-depth-camera-touch-screen-support-slam-mapping-navigation-advanced-kit
JetTank Tutorial: https://drive.google.com/drive/folders/1He-rSE7MOkY1K-oMUG1vHnlu-p1ujKNz?usp=sharing
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JetTank is a ROS tank robot tailored for ROS learning. It is loaded with NVIDIA Jetson Nano, high-performance encoder motor, Lidar, 3D depth camera and 7-inch LCD screen, which open 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 JetTank 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!
1. Lidar Functions
1) 2D Lidar Mapping and Navigation — 2D Lidar Mapping and Navigation
JetTank 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 — JetTank 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, JetTank 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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2. Depth Camera Functions
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 JetTank to navigate and avoid obstacle in 3D map, as well as re-locate 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, JetTank can get depth map, color image and point cloud of the camera.
4) MediaPipe Development, Upgraded AI Interaction — Based on MediaPipe framework, JetTank can carry out human body recognition, fingertip detection, face detection, 3D detection and more.
5) Deep Learning, Autonomous Driving — With JetTank, you can design an autonomous driving scenario to put ROS into practice, which enables you to better understand core functions of autonomous driving.
① Road Sign Detection — Through training deep learning model library, JetTank can realize autonomous driving with AI vision.
② Lane Keeping — JetTank is capable of recognizing the lanes on both sides to maintain safe distance between it and the lanes.
③ Traffic Light Detection — JetTank determines whether go or stop through recognizing the traffic light.
④ AI Deep Learning Framework — Utilize YOLO network algorithm and deep learning model library to recognize the objects.
⑤ KCF Target Tracking — Relying on KCF filtering algorithm, the robot can track the selected target.
⑥ Color/Tag Recognition and Tracking — JetTank is able to recognize and track the designated color, and can recognize multiple AprilTag and their coordinates at the same time.
⑦ Augmented Reality (AR) — After you select the patterns on the APP, the patterns can be overlaid on the AprilTag.
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3. 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
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4. Interconnected Motorcade
1) Multi-vehicle Navigation — Depending on multi-machine communication, JetTank can achieve multi-vehicle navigation, path planning and smart obstacle avoidance.
2) Intelligent Formation — A batch of JetTank cars can maintain the formation, including horizontal line, vertical line and triangle, during moving.
3) Group Control — A group of JetTank can be controlled by only one wireless handle to perform actions uniformly and simultaneously.
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5. 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.
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6. Gazebo Simulation
JetTank employs ROS framework and supports Gazebo simulation. Gazebo brings a fresh approach for you to control JetTank and verify the algorithm in simulated environment, which reduces experimental requirements and improves efficiency.
1) JetTank 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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7. Various Control Methods
1) WonderAi APP 2)Map Nav APP (Android Only) 3)Wireless Handle
