Reducing Uncertainty Using Placement and Regrasp Planning on a
Triangular Corner Fixture
Abstract
This paper presented an regrasp planning method to eliminate grasp
uncertainty while considering the geometric constraints of a fixture.
The method automatically finds the Stable Placement Poses (SPPs) of an
object on a Triangular Corner Fixture (TCF), elevates the object from
its SPPs to dropping poses and finds the Deterministic Dropping Poses
(DDPs), builds regrasp graphs by using the SPP-DDP pairs and their
associated grasp configurations, and searches the graph to find regrasp
motion sequences for precise assembly. Since the SPPs and their
associated regrasps are constrained by the TCF’s geometry and have high
precision, the final object poses regrasped via it has low uncertainty
and can be directly used for assembly by position control. In the
experimental section, we study the performance of analytical and
learning-based methods for estimating the DDPs of different objects and
quantitatively examine the proposed method’s ability to suppress
uncertainty using assembly tasks like peg-in-hole insertion and
sheathing tubes, aligning holes, mounting bearing housings, etc. The
results demonstrate the method’s robustness and efficacy.