解决牵引车-挂车机器人视觉稳定与拼接难题

Tractor-trailer wheeled robots need to perform comprehensive perception tasks to enhance their operations in areas such as logistics parks and long-haul transportation. The perception of these robots faces three major challenges: the asynchronous vibrations between the tractor and trailer, the relative pose change between the tractor and trailer, and the significant camera parallax caused by the large size. In this paper, we employ the Dual Independence Stabilization Motion Field Estimation method to address asynchronous vibrations between the tractor and trailer, effectively eliminating conflicting motion estimations for the same object in overlapping regions. We utilize the Random Plane-based Stitching Motion Field Estimation method to tackle the continuous relative pose changes caused by the articulated hitch between the tractor and trailer, thus eliminating dynamic misalignment in overlapping regions. Furthermore, we apply the Unified Vertex Motion Estimation method to manage the challenges posed by the tractor-trailer's large physical size, which results in severely low overlapping regions between the tractor and trailer views, thus preventing distortions in overlapping regions from exponentially propagating into non-overlapping areas. Furthermore, this framework has been successfully implemented in real tractor-trailer wheeled robots. The proposed Unified Vertex Motion Video Stabilization and Stitching method has been thoroughly tested in various challenging scenarios, demonstrating its accuracy and practicality in real-world.