SummaryDetermining an appropriate grasp configuration for multi-finger grasping is difficult due to the complexity of robotic hands. The multi-finger grasp planning should consider not only geometry constraints of objects but also kinematics and dynamics of robotic hand. In this paper, a precision grasp-planning framework is presented for multi-finger hand to grasp unknown objects. First, the manipulation capabilities of the robotic hand are analyzed. The analysis results are further used as bases for the precision grasp planning. Second, the superquadric (SQ) fitting method is used for approximating unknown object models. Finally, a local–global optimization method is implemented to find appropriate grasp configurations for dexterous hand. The presented planning framework is validated in simulation experiments. Simulation results demonstrated that the presented grasp-planning framework enables the multi-finger hand to grasp unknown objects effectively.

Since human hands have complex anatomical structure and are hard to be duplicated, lots of researches have been done to simplify it by gesture analysis, functional workspace evaluation and many other approaches. In this article, a novel light-duty four-finger hand driven by tendons is presented. The design is based on principal components analysis theory in order to reduce the minor degrees of freedom and lower the mechanism complexity. Meanwhile, optimization of the structure parameters is carried out with respect to the analyses of grasp ability and the single finger's dexterity. A few simple and explicit indices are defined to evaluate the hand properties. In addition, this article also discusses the tendon routing method to realize the accuracy control of the tendon-driven hand's joints. The approach presented in this article can be easily implemented on other mechanical hand platforms and assist the grasp planning in further works.