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 face three major challenges: the relative pose change between the tractor and trailer, the asynchronous vibrations between the tractor and trailer, and the significant camera parallax caused by the large size. In this paper, we propose a novel Unified Vertex Motion Video Stabilization and Stitching framework designed for unknown environments. To establish the relationship between stabilization and stitching, the proposed Unified Vertex Motion framework comprises the Stitching Motion Field, which addresses relative positional change, and the Stabilization Motion Field, which tackles asynchronous vibrations. Then, recognizing the heterogeneity of optimization functions required for stabilization and stitching, a weighted cost function approach is proposed to address the problem of camera parallax. 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 robot tasks.

翻译：牵引挂车式轮式机器人需执行全面的感知任务以提升其在物流园区、长途运输等领域的作业效能。这类机器人的感知面临三大挑战：牵引车与挂车间的相对位姿变化、牵引车与挂车间的异步振动，以及因庞大尺寸导致的显著相机视差。本文提出一种面向未知环境的新型统一顶点运动视频稳像与拼接框架。为建立稳像与拼接间的关联，所提出的统一顶点运动框架包含处理相对位置变化的拼接运动场，以及应对异步振动的稳像运动场。随后，针对稳像与拼接所需优化函数的异质性，提出加权代价函数方法以解决相机视差问题。此外，该框架已在真实牵引挂车式轮式机器人上成功部署。所提出的统一顶点运动视频稳像与拼接方法已在多种挑战性场景中经过全面测试，验证了其在真实机器人任务中的准确性与实用性。