SKU:jettank
Hiwonder
Hiwonder JetTank ROS Robot Tank Powered by Jetson Nano with Lidar Depth Camera Touch Screen, Support SLAM Mapping and Navigation
Hiwonder JetTank ROS Robot Tank Powered by Jetson Nano with Lidar Depth Camera Touch Screen, Support SLAM Mapping and Navigation
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Overview
The Hiwonder JetTank ROS Robot Tank Powered by Jetson Nano with Lidar Depth Camera Touch Screen, Support SLAM Mapping and Navigation is a Hiwonder lidar selected for robotics, AI, automation, and engineering development. It is suited for mapping, SLAM, localization, and autonomous navigation across mobile robots, research platforms, AMRs, and ROS-based robotics systems. Kinematic Supply lists this product as part of a growing robotics component catalog to help builders compare parts, source components, and move faster from prototype to working system.
Applications
- Supports ROS-focused robotics development and experimentation
- Designed for NVIDIA Jetson-based AI and robotics workflows
- Useful for vision, perception, object recognition, and navigation tasks
- Appropriate for SLAM, mapping, localization, and autonomous navigation
Product Details
Smart ROS Robots Driven by AI: JetTank supports Robot Operating System (ROS). It leverages mainstream deep learning frameworks, incorporates MediaPipe development, enables YOLO model training. This combination delivers 3D machine vision applications, including autonomous driving, somatosensory interaction and KCF target tracking. SLAM Development and Diverse Configuration: Hiwonder JetTank is equipped with a 3D depth camera and Lidar. It utilizes a wide range of advanced algorithms including gmapping, hector, karto and cartographer, enabling precise multi-point navigation, TEB path planning, and dynamic obstacle avoidance. High-performance Hardware Configurations: JetTank is made of aluminum.
Why Buy from Kinematic Supply?
Kinematic Supply helps robotics teams discover and source motors, actuators, sensors, cameras, controllers, robot kits, and related components from one growing catalog.
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