scholarly journals Grasping Force Optimization Approaches for Anthropomorphic Hands

2017 ◽  
Vol 10 (1) ◽  
Author(s):  
Aimee Cloutier ◽  
James Yang
Keyword(s):  
Computational Efficiency ◽  
Linear Method ◽  
Contact Forces ◽  
Applied Force ◽  
Contact Friction ◽  
Linear Matrix ◽  
Human Hand ◽  
Contact Points ◽  
Force Optimization ◽  
Grasping Force

An appropriate choice of contact forces for anthropomorphic robotic grasping devices 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 (GFO) in the literature can be difficult to compare due to variability in the parameters, such as the type of grasping device, the object grasped, and the contact model, among other factors. Additionally, methods are typically tested on a very small number of scenarios and may not be as robust in other settings. This paper presents a detailed analysis of three optimization approaches based on the literature, comparing them on the basis of accuracy and computational efficiency. 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 (SF) contact and hard finger (HF) contact friction models. For each method and grasping example, an external force is applied to the object in eighteen different directions to provide a more complete picture of the methods' performance. Contact points between the hand and the object are predetermined (given). A comparison of the results showed that the nonlinear and linear matrix inequality (LMI) approaches perform best in terms of accuracy, while the computational efficiency of the linear method is stronger unless the number of contact points and segments becomes too large. In this case, the nonlinear method performs more quickly. Future work will extend the problem of GFO to real-time implementation, and a related work (briefly addressed here) examines the sensitivity of optimization methods to variability in the contact locations.

Force Optimization Approaches for Common Anthropomorphic Grasps

2016 ◽  
Author(s):  
Aimee Cloutier ◽  
James Yang
Keyword(s):  
Point Contact ◽  
Contact Forces ◽  
Applied Force ◽  
Linear Matrix ◽  
Human Hand ◽  
Numerical Examples ◽  
Contact Points ◽  
Force Optimization ◽  
Grasping Forces ◽  
Grasping Force

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.

Examining the Robustness of Grasping Force Optimization Methods Using Uncertainty Analysis

2018 ◽  
Vol 4 (4) ◽  
Author(s):  
Aimee Cloutier ◽  
James Yang
Keyword(s):  
Center Of Mass ◽  
Linear Method ◽  
Optimization Methods ◽  
Linear Matrix ◽  
Human Hand ◽  
Nonlinear Method ◽  
Object A ◽  
Force Optimization ◽  
Grasping Force ◽  
Robotic Devices

The development of robust and adaptable methods of grasping force optimization (GFO) is an important consideration for robotic devices, especially those which are designed to interact naturally with a variety of objects. Along with considerations for the computational efficiency of such methods, it is also important to ensure that a GFO approach chooses forces which can produce a stable grasp even in the presence of uncertainty. This paper examines the robustness of three methods of GFO in the presence of variability in the contact locations and in the coefficients of friction between the hand and the object. A Monte Carlo simulation is used to determine the resulting probability of failure and sensitivity levels when variability is introduced. Two numerical examples representing two common grasps performed by the human hand are used to demonstrate the performance of the optimization methods. Additionally, the method which yields the best overall performance is also tested to determine its consistency when force is applied to the object's center of mass in different directions. The results show that both the nonlinear and linear matrix inequality (LMIs) methods of GFO produce acceptable results, whereas the linear method produces unacceptably high probabilities of failure. Further, the nonlinear method continues to produce acceptable results even when the direction of the applied force is changed. Based on these results, the nonlinear method of GFO is considered to be robust in the presence of variability in the contact locations and coefficients of friction.

Sensing and Force-Feedback Exoskeleton Robotic (SAFER) Glove Mechanism for Hand Rehabilitation

2015 ◽  
Author(s):  
Zhou Ma ◽  
Pinhas Ben-Tzvi ◽  
Jerome Danoff
Keyword(s):  
Force Feedback ◽  
Force Sensor ◽  
Gaussian Mixture ◽  
Contact Forces ◽  
Learning System ◽  
Human Hand ◽  
Hand Rehabilitation ◽  
Mixture Regression ◽  
Grasping Force ◽  
Force Contact

This paper presents the design and application of the SAFER glove in the field of hand rehabilitation. The authors present preliminary results on a new hand grasping rehabilitation learning system that is designed to gather kinematic and force information of the human hand and to playback the motion to assist a user in common hand grasping movements, such as grasping a bottle of water. The fingertip contact forces during grasping have been measured by the SAFER Glove from 12 subjects. The measured fingertip contact forces were modeled with Gaussian Mixture Model (GMM) based on machine learning approach. The learned force distributions were then used to generate fingertip force trajectories with a Gaussian Mixture Regression (GMR) method. To demonstrate the glove’s potential to manipulate the hand, experiments with the glove fitted on a wooden hand to grasp various objects were performed. Instead of defining a grasping force, contact force trajectories were used to control the SAFER Glove to actuate/assist this hand while carrying out a learned grasping task. To prove that the hand can be driven safely by the haptic mechanism, force sensor readings placed between each finger and the mechanism have been plotted. The experimental results show the potential of the proposed system in future hand rehabilitation therapy.

The Design Evolution of a Sensing and Force-Feedback Exoskeleton Robotic Glove for Hand Rehabilitation Application

2016 ◽  
Vol 8 (5) ◽  
Author(s):  
Pinhas Ben-Tzvi ◽  
Jerome Danoff ◽  
Zhou Ma
Keyword(s):  
Contact Force ◽  
Force Feedback ◽  
Gaussian Mixture ◽  
Contact Forces ◽  
Human Hand ◽  
Hand Rehabilitation ◽  
Mixture Regression ◽  
Design Evolution ◽  
Grasping Force ◽  
Force Contact

This paper presents the design evolution of the sensing and force-feedback exoskeleton robotic (SAFER) glove with application to hand rehabilitation. The hand grasping rehabilitation system is designed to gather kinematic and force information from the human hand and then playback the motion to assist a user in common hand grasping movements, such as grasping a bottle of water. Grasping experiments were conducted where fingertip contact forces were measured by the SAFER glove. These forces were then modeled based on a machine learning approach to obtain the learned contact force distributions. Using these distributions, fingertip force trajectories were generated with a Gaussian mixture regression (GMR) method. To demonstrate the glove's effectiveness to manipulate the hand, experiments were performed using the glove to demonstrate grasping capabilities on several objects. Instead of defining a grasping force, contact force trajectories were used to control the SAFER glove in order to actuate a user's hand while carrying out a learned grasping task.

scholarly journals Design and Calibration of a Force/Tactile Sensor for Dexterous Manipulation

Sensors ◽  
2019 ◽  
Vol 19 (4) ◽  
pp. 966 ◽  
Author(s):  
Marco Costanzo ◽  
Giuseppe De Maria ◽  
Ciro Natale ◽  
Salvatore Pirozzi
Keyword(s):  
Experimental Validation ◽  
Sensory System ◽  
Tactile Sensor ◽  
Contact Forces ◽  
Dexterous Manipulation ◽  
Soft Contact ◽  
Grasping Force ◽  
Sense Of Touch ◽  
Human Sense ◽  
Robotic Applications

This paper presents the design and calibration of a new force/tactile sensor for robotic applications. The sensor is suitably designed to provide the robotic grasping device with a sensory system mimicking the human sense of touch, namely, a device sensitive to contact forces, object slip and object geometry. This type of perception information is of paramount importance not only in dexterous manipulation but even in simple grasping tasks, especially when objects are fragile, such that only a minimum amount of grasping force can be applied to hold the object without damaging it. Moreover, sensing only forces and not moments can be very limiting to securely grasp an object when it is grasped far from its center of gravity. Therefore, the perception of torsional moments is a key requirement of the designed sensor. Furthermore, the sensor is also the mechanical interface between the gripper and the manipulated object, therefore its design should consider also the requirements for a correct holding of the object. The most relevant of such requirements is the necessity to hold a torsional moment, therefore a soft distributed contact is necessary. The presence of a soft contact poses a number of challenges in the calibration of the sensor, and that is another contribution of this work. Experimental validation is provided in real grasping tasks with two sensors mounted on an industrial gripper.

scholarly journals Slipping–rolling transitions of a body with two contact points

2021 ◽  
Author(s):  
Mate Antali ◽  
Gabor Stepan
Keyword(s):  
Rigid Body ◽  
Contact Point ◽  
Static Friction ◽  
Rigid Body Dynamics ◽  
Contact Forces ◽  
Friction Forces ◽  
Contact Points ◽  
Body Dynamics ◽  
Coulomb Model ◽  
Rigid Surfaces

AbstractIn this paper, the general kinematics and dynamics of a rigid body is analysed, which is in contact with two rigid surfaces in the presence of dry friction. Due to the rolling or slipping state at each contact point, four kinematic scenarios occur. In the two-point rolling case, the contact forces are undetermined; consequently, the condition of the static friction forces cannot be checked from the Coulomb model to decide whether two-point rolling is possible. However, this issue can be resolved within the scope of rigid body dynamics by analysing the nonsmooth vector field of the system at the possible transitions between slipping and rolling. Based on the concept of limit directions of codimension-2 discontinuities, a method is presented to determine the conditions when the two-point rolling is realizable without slipping.

Periodic Response of a Link Coupling With Clearance

1989 ◽  
Vol 111 (2) ◽  
pp. 253-259 ◽  
Author(s):  
Y. S. Choi ◽  
S. T. Noah
Keyword(s):  
Steady State ◽  
Boundary Conditions ◽  
Solution Procedure ◽  
Contact Forces ◽  
Steady State Response ◽  
Algebraic Equations ◽  
State Response ◽  
Contact Points ◽  
Integration Schemes ◽  
Nonlinear Algebraic Equations

The nonlinear, steady-state response of a displacement-forced link coupling with clearance with finite stiffness is determined. The solution procedure is derived from satisfying the boundary conditions at the contact points and then solving the resulting nonlinear algebraic equations by setting the duration of contact as a parameter. This direct approach to determining periodic solutions for systems with clearances with finite stiffness is substantially more efficient than numerical integration schemes. Results in terms of contact forces and durations of contact are pertinent to fatigue and wear studies. Parametric relations are presented for effects of the variation of damping, stiffness, exciting displacement, and gap length on the dynamic behavior of the link pair.

RTCONTACT: An Efficient Wheel-Rail Contact Algorithm for Real-Time Dynamic Simulations

2012 ◽  
Author(s):  
N. Bosso ◽  
A. Gugliotta ◽  
N. Zampieri
Keyword(s):  
Real Time ◽  
Computational Efficiency ◽  
Simulation Models ◽  
Experimental Tests ◽  
Contact Forces ◽  
Dynamic Simulations ◽  
Time Dynamic ◽  
Contact Algorithm ◽  
Complex Simulation ◽  
Precise Representation

Determination of contact forces exchanged between wheel and rail is one of the most important topics in railway dynamics. Recent studies are oriented to improve the existing contact methods in terms of computational efficiency on one side and on the other side to develop more complex and precise representation of the contact problem. This work shows some new results of the contact code developed at Politecnico di Torino identified as RTCONTACT; this code, which is an improvement of the CONPOL algorithm, is the result of long term activities, early versions were used in conjunction with MBS codes or in Matlab® environment to simulate vehicle behaviour. The code has been improved also using experimental tests performed on a scaled roller-rig. More recently the contact model was improved in order to obtain a higher computational efficiency that is a required for the use inside of a Real Time process. Benefit of a Real Time contact algorithm is the possibility to use complex simulation models in diagnostic or control systems in order to improve their performances. This work shows several comparisons of the RTCONTACT contact code respect commercial codes, standards and benchmark results.

Estimation of Graphite Dust Production in a Pebble-Bed Type Nuclear Reflector

2014 ◽  
Author(s):  
Ji-Ho Kang ◽  
Eung Seon Kim ◽  
Seungyon Cho
Keyword(s):  
Adhesive Wear ◽  
Cell Model ◽  
Estimation Method ◽  
Unit Cell ◽  
Contact Forces ◽  
Dust Explosion ◽  
Dust Production ◽  
Pebble Bed ◽  
Normal Contact ◽  
Contact Points

In this study, an estimation method of graphite dust production in the pebble-bed type reflector region of Korean HCSB (Helium-Cooled Solid Breeder) TBM (Test Blanket Module) in the ITER (International Thermonuclear Experimental Reactor) project using FEM (Finite Element Method) was proposed and the amount of dust production was calculated. A unit-cell model of uniformly arranged pebbles was defined with appropriate thermal and mechanical loadings. A commercial FEM program, Abaqus V6.10 was used to model and solve the stress field under multiple contact constraints between pebbles in the unit-cell. Resulting normal contact forces and slip distances on contact points were applied into the Archard adhesive wear equation to calculate the amount of graphite dust. The friction effect on contact points was investigated. The calculation result showed that the amount of graphite dust production was estimated to 2.22∼3.67e−4 g/m3 which was almost linearly proportional to the friction coefficient. The analysis results will be used as the basis data for the consecutive study of dust explosion.

Sign in / Sign up

Export Citation Format

Share Document