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ROS Robot

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  • 【Classic Ackermann Steering Structure】JetAcker is built upon an Ackermann chassis providing an opportunity to learn and validate robots based on the Ackermann steering structure.
  • 【Dive in AI Algorithm and Smart Robotics】JetAcker runs on NVIDIA Jetson Nano B01, supports ROS, utilizes deep learning frameworks, MediaPipe, YOLO training, and TensorRT acceleration for diverse 3D machine vision applications.
  • 【SLAM Development and Diverse Configuration】JetAcker is equipped with a 3D depth camera and Lidar, enabling remote communication, precise 2D mapping navigation, TEB path planning, and dynamic obstacle avoidance. 
  • 【Robot Control Across Platforms】JetAcker provides multiple control methods, like WonderAi app (compatible with iOS and Android system), wireless handle, Robot Operating System (ROS) and keyboard.
  • 【Detailed Tutorials and Professional After-sales Service】We offer an extensive collection of tutorials, covering wide range of topics, including getting ready, Linux operating system, ROS, OpenCV, depth camera and Lidar mapping navigation, autonomous driving, 3D vision interaction and voice interaction courses.
  • 【High-performance Hardware Configurations】JetAcker features an aluminum alloy bracket, CNC steering, and a range of hardware: 100mm rubber wheels, 520 Hall encoder motors, Lidar, ORBBEC Astra Pro Plus camera, 240° pan-tilt, multi-functional expansion board, motor driver, and 11.1V 6000mAh Lipo battery.
  • 【Support Secondary Development】You can utilize the existing learning tutorials to carry out secondary development. Please note that our technical support is limited to the existing learning tutorials.
  • Powered by NVIDIA Jetson Nano and based on ROS
  • Support depth camera and Lidar 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
  • Powered by Jetson Nano(included)
  • Open source and based on ROS
  • Deep learning, model training, inverse kinematics
  • Abundant sensors for function expansion
  • Changeable robot models with mecanum wheel chassis or sliding rail
  • 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
  • Optional 6-microphone array for voice interaction
  • Open-source, ample PDF materials and tutorials are provided
  • Powered by NVIDIA Jetson Nano and based on ROS
  • Support depth camera and Lidar 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
  • Powered by Raspberry Pi 4B/ CM4 (included in the kit) and based on ROS
  • Equipped with HD wide-angle camera
  • Support FPV transmitted image
  • Powerful vehicle chassis for omni-directional movement
  • Open Source and abundant tutorial materials
  • Powered by NVIDIA Jetson Nano and based on ROS
  • Support depth camera and Lidar for mapping and navigation
  • Upgraded inverse kinematics algorithm
  • Capable of deep learning and model training
  • Open source and provide ample PDF materials and tutorials
  • Powered by Raspberry Pi 4B/ CM4 and based on ROS
  • Capable of gait planning and adopt linkage kinematics
  • Possess machine vision and work with OpenCV
  • Support Gazebo simulation
  • Ample tutorials and open-source codes are provided
  • Jetson Nano is included in the kit
  • Open-Source, First Person Vision
  • Inverse Kinematics, ROS
  • Deep learning, Model training
  • Multiple Extended Functions
  • Powered by Raspberry Pi 4B/ CM4 which is optional
  • Equipped with HD wide-angle camera
  • FPV vision for facial recognition, tag recognition etc
  • ROS robot operating system and inverse kinematics
  • PC software, phone App and VNC remote desktop control
  • Provide Python source code
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