Three important problems in the study of grasping and manipulation by multifingered robotic hands are: (a) Given a grasp characterized by a set of contact points and the associated contact models, determine if the grasp has force closure; (b) If the grasp does not have force closure, determine if the ngers are able to apply a specified resultant wrench on the object; and (c) Compute "optimal" contact forces if the answer to problem (b) is affirmative. In this paper, based on an early result by Buss, Hashimoto and Moore, which transforms the nonlinear friction cone constraints into positive definiteness of certain symmetric matrices, we further cast the friction cone constraints into linear matrix inequalities (LMIs) and formulate all three of the problems stated above as a set of convex optimization problems involving LMIs. The latter problems have been extensively studied in optimization and control community and highly efficient algorithms with polynomial time complexity are now available for their solutions. We perform simulation studies to show the simplicity and efficiency of the LMI formulation to the three problems.

In this paper we propose a novel approach to reference behavior specification for multiple robotic mechanisms using hybrid system models. Hybrid automata can specify discrete states (operational modes) and continuous variable reference values in one unified framework. An example mechanism with 3 degrees-offreedom and a 6-legged walking machine with a combination of several hybrid automata for reference generation and synchronization are discussed. Simulation results show that a hybrid system model is an effective method for robotic behavior specification. Using a model verification tool we show that behavior correctness verification and parametric analysis are possible. 1 Introduction Multiple robotic mechanisms have been investigated to realize more flexible and complex behavior otherwise not achievable with single robots. Active research areas are cooperating robot manipulators which may carry heavy loads [1], dextrous multifingered hands which are used for complex manipulation tas...

In this paper we present a real-time algorithm for optimization of contact forces during precision grasping. The algorithm keeps contact forces as small as possible while obeying fricition limits at the contact points. Contact force trajectories are smooth even during regrasping tasks by lifting o# and recontacting fingers. Necessary grasp parameters are calculated from force sensor data on run-time. Keywords: robust extrous grasping, real-time grasping force optimization, regrasping 1 Introduction Most of the previously proposed approaches for optimization of grasping forces are based on linear programming methods and are, in general, not well-suited for on-line applications. A straightforward adaptation of grasp forces based on force sensor data in real-time was suggested by [1]. In [2] a solution based on gradient flows on the smooth manifold of positive definite matrices was presented, simplified versions of which were applied in experiments [3,4]. Now we present a comprehensive ...

A real-time applicable grasping force optimization scheme for stable dextrous grasping has been proposed earlier. In this paper we present a novel approach to planning multi-fingered regrasping based on a modification of the optimization algorithm. This novel algorithm allows for smooth grasping force transitions during regrasping tasks. The optimization scheme is implemented combined with an impedance control law. Simulation results show the efficiency and simplicity of our approach to regrasping.

In the field of research and development of grippers in object-handling applications, many research results in improving grippers' performances have been achieved, and many kinds of multifinger grippers have been developed. By using multifinger grippers, it is possible to grasp different objects of different shapes without changing grippers; and most importantly, it can manipulate the grasped object in the hand, under the condition that the object is controlled in real-time. Therfore, an object-pose controller with feedback from an object-pose sensor is presented in this paper.