In this paper, we propose a new approach for computing force-closure grasps of two-dimensional and threedimensional objects. Assuming n hard-finger contact with Coulomb friction model and based on central axes of the grasp wrench (i.e., force and torque), we develop a new necessary and sufficient condition for n-finger grasps to achieve force-closure. We demonstrate that a grasp is force-closure if and only if, its wrench can generate any arbitrary central axis. According to this condition, we reformulate the force-closure test as a linear programming problem without computing the convex hull of the primitive contact wrenches. Therefore, we present an efficient algorithm for computing n-finger force-closure grasps. Finally, we have implemented the proposed algorithm and verified its efficiency through some examples.
SUMMARYThis paper addresses the dimensional-synthesis-based kineto-elastostatic performance optimization of thedeltaparallel mechanism. For the manipulator studied here, the main consideration for the optimization criteria is to find the maximum regular workspace where the robotdeltamust posses high stiffness and dexterity. The dexterity is a kinetostatic quality measure that is related to joint's stiffness and control accuracy. In this study, we use the Castigliano's energetic theorem for modeling the elastostatic behavior of thedeltaparallel robot, which can be evaluated by the mechanism's response to external applied wrench under static equilibrium. In the proposed formulation of the design problem, global structure's stiffness and global dexterity are considered together for the simultaneous optimization. Therefore, we formulate the design problem as a multi-objective optimization one and, we use evolutionary genetic algorithms to find all possible trade-offs among multiple cost functions that conflict with each other. The proposed design procedure is developed through the implementation of thedeltarobot and, numerical results show the effectiveness of the proposed design method to enhancing kineto-elastostatic performance of the studied manipulator's structure.
In this paper, we propose an approach for computing suboptimal grasps of polyhedral objects. Assuming n hard-finger contact with Coulomb friction model and based on central axes of the grasp wrench, we develop a new necessary and sufficient condition for n-finger grasps to achieve force-closure property. Accordingly, we reformulate the proposed force-closure test as a new linear programming problem, which we solve using an interior point method. Furthermore, we present an approach for finding appropriate stable grasps for a robotic hand on arbitrary objects. We use the simulated annealing technique for synthesizing suboptimal grasps of 3D objects. Through numerical simulations on arbitrary shaped objects, we show that the proposed approach is able to compute good grasps for multifingered hands within a reasonable computational time.
Improvised Explosive Devices (IEDs) represent a serious threat to vehicles. These IEDs can partially or fully damage the vehicle and the onboard equipment and, threaten the lives of its crew. To protect against these devices, modifications to specialized vehicles are made in different parts. Among these latter, the present work focuses on the effects of the suspension system on the dynamic response of the vehicle. The behaviour of a McPherson suspension system of a light vehicle is numerically studied in order to optimize the dimensions of selected components. Three models based on different approaches are developed. The first is based on an Arbitrary Lagrangian Eulerian (ALE) formulation with fluid-structure coupling, which gives a more realistic representation of the blast phenomena. However, it needs significant calculation time and computational power. The second is a simplified, purely Lagrangian, model which requires less computational resources but includes several assumptions. The third model is based on a meta-modelling approach. This latter is used to optimize the dimensions of selected sub-systems of the vehicle suspension via a genetic optimization algorithm.
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