Most welding manufacturing of the heavy industry, such as shipbuilding and construction, is carried out in an unstructured workspace. The term Unstructured indicates the production environment is irregular, changeable and without model. In this case, the changeable workpiece position, workpiece shape, environmental background, and environmental illumination should be carefully considered. Because of such complicated characteristics, the welding is currently being relied on the manual operation, resulting in high cost, low efficiency and quality. This work proposes a portable robotic welding system and a novel seam tracking method. Compared to existing methods, it can cope with more complex general spatial curve weld. Firstly, the tracking pose of the robot is modeled by a proposed dual-sequence tracking strategy. On this basis, the working parameters can be adjusted to avoid robot-workpiece collision around the workpiece corners during the tracking process. By associating the forward direction of the welding torch with the viewpoint direction of the camera, Robotic autonomous welding it solves the problem that the weld feature points are prone to be lost in the tracking process by conventional methods. Point cloud registration is adopted to globally locate the multi-segment welds in the workpiece, since the system deployment location is not fixed. Various experiments on single or multiple welds under different environmental conditions show that even if the robot is deployed in different positions, it can reach the starting point of the weld smoothly and accurately track along the welds.