loading page

Reducing Uncertainty Using Placement and Regrasp Planning on a Triangular Corner Fixture
  • +1
  • Zhengtao Hu ,
  • Weiwei Wan ,
  • Keisuke Koyama ,
  • Kensuke Harada
Zhengtao Hu
Author Profile
Weiwei Wan
Author Profile
Keisuke Koyama
Author Profile
Kensuke Harada
Author Profile


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.
2023Published in IEEE Transactions on Automation Science and Engineering on pages 1-19. 10.1109/TASE.2023.3234047