JETSON/RK3588+FPGA+AI-based Commercial Autonomous Mowing Robot Solution

Scenario Requirements: Currently, comprehensive solutions for commercial autonomous mowing robots are still in the preliminary research phase. For research teams and developers, the core demand centers on a visual perception solution tailored for mowing scenarios: This solution needs to efficiently handle complex environments such as varying lighting, diverse obstacles, and ambiguous boundaries in unstructured lawns. It must be cost-effective, open, and easy to develop, supporting intensive algorithm iteration and ground truth validation. Furthermore, it must reliably achieve three core capabilities: real-time semantic segmentation, obstacle recognition, and precise boundary determination, thereby accelerating the transition from laboratory prototypes to stable products.     

Product Application: The robotic stereo camera integrates a global shutter, 720P resolution, and stereo vision capabilities within a limited budget. It can acquire high-precision depth information in real-time, accurately perceiving lawn terrain and obstacles, thus meeting the precise perception requirements for real-time obstacle avoidance and navigation in mowing robots. The machine vision GMSL camera features high dynamic range imaging, enabling it to adapt to complex lighting changes in grassy environments. This significantly reduces system integration and development costs, making it suitable for fundamental visual applications in mowing robots.