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is not so much based on the expected grasping quality but more on the spatial arrangement of the scene as a
whole. To give two examples: If a box is located on top of a truncated square pyramid, one will first take away
the box without spending time on trying to figure out how to grasp the underlying pyramid (in fact, even the
grasping of the pyramid may not be possible if the surface is slippery and/or the pyramid is too flat). A second
example is the situation where there are two separated objects (i.e., located far away from each other). Here
one normally concentrates on the closer object without inspecting the other one. It seems that we first select
the object and then decide how to grasp it.
So we think that it is reasonable to divide the task of removing heaps of objects into the following two subprob-
lems: the search for an adequate object to be removed next, and the finding of grasping opportunities for the
selected object. The next two sections will describe these two processes in more detail.
4.1 Object Selection
As already mentioned, one of the factors determining the selection of an object to be removed is the spatial
arrangement of the scene. The following two main rules guide the decision process:
- First of all we want to limit the effect of our action (the grasping) to the smallest possible area (namely the
object to be removed). This restriction is very closely related to the "focus of attention” paradigm. Here we
may call it “focus of action”. In other words, we want to disturb the scene as little as possible, thus reducing
the possibility of unexpected *movements" ,e.g., the collapse of a pile. As a consequence we will refrain from
removing objects which are covered by others. Otherwise we would not only change the position of the object
to be removed but also that of the objects on top of it (they will fall down).
- Second, we want to simplify the scene as much as possible. Not necessarily with respect to the vision system,
but more with respect to the path planing for the robot. The goal is to allow the robot to move freely between
the disposal area where it may have placed a previous object and the new grasping position. By first removing
objects close to the disposal area we reduce the chance of accidental collisions. This not only simplifies the
movement towards the new object but even more importantly makes the move back with the object in the hand
less error prone. In addition, if the grasp is bad and the object falls down on the way back to the disposal area,
it has less chance to hit another object.
Certainly there are exceptions to these two rules. It can happen that we cannot find grasping points for the
selected object, or a grasping opportunity was found but the robot is not able to perform the action (e.g., the
position is not reachable). In cases like these the object is skipped and marked as “non-graspable”. The next
“best” object is then being considered.
4.2 Grasping Point Determination
After having decided on which object to grasp, we concentrate on the question of how to grasp it. For the case
of a two-finger-gripper with parallel jaws of a certain width, the search for a grasping opportunity involves the
determination of the following features for a pair of vertices and their small neighborhoods of triangles (which
we choose to call patches):
a) there exists a pair of patches the normals of which are roughly antiparallel
b) the patches are in a relation of oppositeness
c) the patches are not too far apart
d) the line joining the two patches passes near the "center of gravity" of the object
e) there is enough clearance for the approach of the gripper jaws
f) the height of the patch pair relative to the base is above a certain threshold
(Grippers with three round fingers or others with just a single suction cup would require the assertion of à
partially different set of features, of course.)
As already mentioned, we consider all possible vertex pairs as candidate point pairs for the grasp. Thus we
have to calculate the above features for all these pairs. The sequence of the pairs is chosen arbitrarily but not
the sequence of the calculation of the features. The reason is that if for a certain vertex pair one feature is
absent, we do not have to calculate the remaining ones anymore, e.g., if two vertices are not in a relation of
oppositeness, then calculating possible collision points for the gripper would be a loss of time. We therefore
order the features according to their computational complexity and to their “selective power”. A feature which
is simple to calculate and recognizes most of the non-suitable vertex pairs, should be placed first in the list. We
IAPRS, Vol. 30, Part 5W1, ISPRS Intercommission Workshop "From Pixels to Sequences", Zurich, March 22-24 1995