Force Optimization Approaches for Common Anthropomorphic Grasps

Abstract

A smart choice of contact forces between robotic grasping devices and objects is important for achieving a balanced grasp. Too little applied force may cause an object to slip or be dropped, and too much applied force may cause damage to delicate objects. Prior methods of grasping force optimization in literature have mostly assumed grasp only at the fingertips but have rarely considered how the whole hand grasps more common to anthropomorphic hands affect the optimization of grasping forces. Further, although numerical examples of grasping force optimization methods are routinely provided, it is often difficult to compare the performance of separate methods when they are evaluated using different parameters, such as the type of grasping device, the object grasped, and the contact model, among other factors. This paper presents three optimization approaches (linear, nonlinear, and nonlinear with linear matrix inequality (LMI) friction constraints) which are compared for an anthropomorphic hand. Numerical examples are provided for three types of grasp commonly performed by the human hand (cylindrical grasp, tip grasp, and tripod grasp) using both soft finger contact and point contact with friction models. Contact points between the hand and the object are predetermined. Results are compared based on their accuracy, computational efficiency, and other various benefits and drawbacks unique to each method. Future work will extend the problem of grasping force optimization to include consideration for variable forces and object manipulation.

Grasping Force Optimization Approaches for Anthropomorphic Hands

“…By contrast, interior point methods, some of which have been implemented in grasping force optimization, are computationally efficient but require an initial feasible solution to start the algorithm. In the previous work, several LP algorithms were tested to determine which method performed the most quickly [1]. Based on this comparison, the LP problem in this paper is solved using the linprog function in MATLAB with the interior point legacy algorithm.…”

“…As an extension of the work in Ref. [1], this paper presents a more thorough examination of three methods of GFO for anthropomorphic hands and for some grasps which have been identified as common in everyday life. Each method is tested for three different grasping scenarios, where the external force is applied to the object in eighteen different directions.…”

“…The purpose of this research is to perform a more detailed analysis of several possible grasping force optimization approaches as an extension of the work presented in Ref. [1]. The benefits and drawbacks unique to each method are compared to determine which approaches are most appropriate for determining contact forces.…”

“…Currently available GFO approaches can be difficult to compare due to variable factors in the optimization approaches and in the numerical examples (e.g., object type, number of contact points, number of fingers, and contact model). In the previous work [1], the authors presented a basic examination of three methods of grasping force optimization: a linear method, a nonlinear method, and a linear matrix inequality method. As an extension of the work in Ref.…”

“…Next, the development of each specific optimization method from Ref. [1] is given. The three numerical examples are shown, along with the directions of applied forces for each example, and the sensitivity of methods with respect to variability in contact locations is briefly addressed.…”