该软件，感觉是偏向于抓取构型以及抓取质量分析方面，目前了解好像不涉及动力学吧。
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手爪有关函数：
SG3Fingered - a three fingered robotic hand
三指barretthand的手爪模型
用法：hand= SG3Fingered
另外，还有模型如
SGDLRHandII - model of the DLR hand II
SGhuman24 - a 24 DoF model of the human hand
SGmodularhand - the model of a three-fingered, 9 DoF modular hand
SGparadigmatic - a 20 DoF model of the human hand
SGunderActuated1 - model of an underactuated robotic hand
用法同三指barretthand手一样，返回hand手爪结构。
如果想自己搭建手爪模型，可以有
SGmakehand - Create a hand
Usage: hand = SGmakehand(F)
Arguments:
F = array of finger structures defined by SGmakeFinger
Returns:
hand = the hand structure
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物体有关：
创建物体：
SGmakeObject - create an object structure for a given hand
This function defines a structure object, given the contact points on the hand, the object center (opt) and the contact normal directions.
Usage: [newHand,object] = SGmakeObject(hand,center,normals) Arguments:
hand: a structure defining the hand structure
center(opt): object center coordinates
normals: directions normal to the contact surface in the contact points
Returns:
newhand: an updated structure of the hand
object: a structure containing object data
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定义一个抓取的方法：
To define a grasp, we have to choose the contact points, as described in the previous chapter. For instance, if we want to simulate a precision grasp with five contact points
on the tips of each finger we can use the following function
hand = SGaddFtipContact(hand,1,1:5);
In the more general case, we can use the function SGaddContact()
hand = SGaddContact(hand,type,cwhere,link,alpha)
As we can observe, hand.cp is a matrix with seven rows and a number of columns equal to the contact points. The first three rows of the matrix contain contact point
coordinates, the fourth one contains an index corresponding to the finger where the contact is, the fifth contains an index representing the link of each finger, where the
contact is, the sixth row specifies the contact type (1 for a hard finger contact model, 2 for a soft finger contact model)
有关函数：
new_hand = SGaddcontact(hand,type,cwhere,link,alpha)
Arguments:
hand = hand structure
type = type of contact
0 - single point without friction
1 - hard finger
2 - soft finger
cwhere = finger index
link = link index
alpha = distance from the link ref origin
Given the contact points on the hand, it is possible to create a structure representing the grasped object through the function SGmakeObject().
The structure for the grasped object contains the object center, contact points and contact normal versors.
The function SGplotObject() can be used to plot a convex object defined by the given contact points. The user can choose the fillet radius and the number of elements for object representation
The grasp planner function SGgraspPlanner() takes as input the hand model, the object to be grasped, the number of pre-grasp positions and the metric to be used for grasp evaluation.
[hand_c,object,b_index] =
SGgraspPlanner(hand,obj,N,qmtype)
Arguments:
hand = the hand structure
obj = the object structure to be grasped
N = the number of random pregrasp
qmtype = the quality metric to be used
Returns:
hand_c = the best hand configuration
object = the grasped object
b_index= the best quality index obtained
这一块具体见 SynGrasp 2.2 Page 16。
确定一个抓取后，可以做什么？
Once the grasp is defined, it is possible to compute all the matrices relevant to grasp analysis.
The evaluation of the selection matrix H, that extracts from the contact point twists the components constrained by the specified contact model, is performed by the function SGselectionMatrix().
The SynGrasp function SGgraspMatrix() allows to evaluate, for a given grasp, the value of the grasp matrix G. The hand Jacobian matrix can be evaluated by means of the function SGjacobianMatrix().
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抓取质量分析：
可抵抗外力螺旋方法
The minimization of SGVcost() function allows to evaluate the set of controllable internal
forces that maximizes the distance from the friction cone boundaries in the contact
points.
可操作问题求解特征值方法
The directions, in the workspace and synergy space,respectively, corresponding to the eigenvectors evaluated solving manipulability problem,are the following
人手写字模型
In SGwritingExample.m a mathematical model of the human hand kinematics able
to describe complex manipulation tasks, such as writing on a tablet with a stylus, is
described
人手协同匹配到机器人手上
Mapping human hand synergies onto robotic hands SynGrasp allows to define hand models with coupled joints activation according to a
defined synergistic organization. While for the paradigmatic hand the synergy subspaces are defined according to the data collect by Santello et al. [12] and can be easily
set using the commands SGsantelloSynergies() and SGdefineSynergies(),
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介绍了一种欠驱动手的并联机构： Page40 on SynGrasp 2.2 toturial
A six DoFs hand actuated with two four linkages mechanisms
我的感觉是，这个地方用到了Barretthand，给出了不同指标下的抓取对比数据。
where MEV stands for manipulability
ellipsoid volume quality index, GII is the grasp isotropy index, MSVG represents
the minimum singular value of the matrix G, DSTC is the distance from the singular
configuration and UOT is the uniformity measure. In Fig. 2.3 the best obtained grasp
using the SGdistSingularConfiguration quality measure is shown.
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