Greetings,
We are Hiwonder, a dedicated team focused on the development of educational robots based on Jetson Nano, Raspberry Pi, Arduino, micro:bit and other controllers.
In the realm of robotics, AI, image processing, and mapping navigation has become a hot subject of discussion. We are thrilled to introduce our latest project, JetAuto, powered by Jetson Nano, which has the potential to enhance learning in these areas.
JetAuto, a robot car based on Robot Operating System (ROS) and powered by NVIDIA Jetson Nano, combines flexibility of a versatile robotics framework with exceptional performance of an embedded platform. Its impressive features include high-performance encoder motors, Lidar, a 3D depth camera, and a 7-inch LCD screen. With this comprehensive suite of capabilities, JetAuto excels in motion control, mapping navigation, path planning, tracking and obstacle avoidance, autonomous driving, human feature recognition, somatosensory interaction, voice interaction, and much more!
By utilizing Lidar, JetAuto is capable of creating an accurate map of its surroundings. Once the map is generated, it can effortlessly navigate to specific points. For a detailed understanding of the mapping and navigation logic employed by JetAuto, we invite you to explore the source code available on our GitHub repository (Repository: JetAuto-ROS-Robot-Car).
By combining the capabilities of Lidar and 3D depth camera, JetAuto excels in accurate 3D mapping and navigation. The integration of YOLOV5 and 3D depth camera further enhances JetAuto’s image processing capabilities. We have published a comprehensive guide on hackster.io (Account: Hammer X Hiwonder) detailing how JetAuto integrates YOLOV5, 3D depth camera, and Jetson Nano board for precise object detection. If you have a keen interest in this fascinating topic, we invite you to explore the post for further insights and information.
Moreover, JetAuto goes beyond a mere mechanical device. Its 6-microphone array enables communication with people, making it an interactive companion.
If you have any kind of question related to this project, please feel free to post a reply. Thank you for taking the time to read this post.
The Hiwonder Team