Abstract: In order to address the low success rate and limited task capability of five-fingered manipulators, a five-fingered grasping system is designed and developed based on regional pose solving, to handle various complex grasping tasks. Firstly, a pneumatic five-fingered soft hand is designed, which is made from various materials with varying levels of stiffness, and is powered by one main and five branch tracheae, offering excellent mechanical and grasping performances, with reduced control complexity, and the ability to implement different grasping strategies. Further, a grasping strategy based on regional pose solving is proposed by considering the characteristics of soft grippers. This strategy generates robust grasping poses by predicting the contact area of the human hand when grasping an object, solving the spatial pose of the contact area and soft hand fingertips, and calculating the grasping pose and bending angle of the soft hand. Then, a contact dataset with a large number of objects is created, marking the contact areas of the human fingertips during grasping the objects in the dataset, and minimizing scene information for increased generality. This dataset can be used as a benchmark to evaluate the performance of different algorithms. Finally, a series of experiments are designed to verify the grasping performance of the five-fingered soft hand and the grasping strategy in complex scenarios. The experimental results demonstrate the effectiveness and reliability of the designed five-fingered soft hand grasping system in complex environments.