Abstract
Handling object deformations for robotic grasping is still a major problem to solve. In this paper, we propose an efficient learning-free solution for this problem where generated grasp hypotheses of a region of an object are adapted to its deformed configurations. To this end, we investigate the applicability of functional map (FM) correspondence, where the shape matching problem is treated as searching for correspondences between geometric functions in a reduced basis. For a user selected region of an object, a ranked list of grasp candidates is generated with local contact moment (LoCoMo) based grasp planner. The proposed FM-based methodology maps these candidates to an instance of the object that has suffered arbitrary level of deformation. The best grasp, by analysing its kinematic feasibility while respecting the original finger configuration as much as possible, is then executed on the object. We have compared the performance of our method with two different state-of-the-art correspondence mapping techniques in terms of grasp stability and region grasping accuracy for 4 different objects with 5 different deformations.
Original language | English |
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Title of host publication | 2022 International Conference on Robotics and Automation (ICRA) |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Pages | 735-741 |
Number of pages | 7 |
ISBN (Electronic) | 9781728196817 |
ISBN (Print) | 9781728196824 (PoD) |
DOIs | |
Publication status | Published - 12 Jul 2022 |
Event | 39th IEEE International Conference on Robotics and Automation, ICRA 2022 - Philadelphia, United States Duration: 23 May 2022 → 27 May 2022 |
Publication series
Name | Proceedings - IEEE International Conference on Robotics and Automation |
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Publisher | IEEE |
ISSN (Print) | 1050-4729 |
ISSN (Electronic) | 2577-087X |
Conference
Conference | 39th IEEE International Conference on Robotics and Automation, ICRA 2022 |
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Country/Territory | United States |
City | Philadelphia |
Period | 23/05/22 → 27/05/22 |
Bibliographical note
Funding Information:This work was supported by the UK National Centre for Nuclear Robotics (NCNR). Part funded by CHIST-ERA under Project EP/S032428/1 Pe-GRoGAM and in part supported by Faraday Institution sponsored Recycling of Lithium Ion Batteries (ReLiB) project (grant: FIRG005).
Publisher Copyright:
© 2022 IEEE.
Keywords
- Frequency modulation
- Shape
- Semantics
- Grasping
- Search problems
- Robot sensing systems
- Stability analysis
ASJC Scopus subject areas
- Software
- Control and Systems Engineering
- Artificial Intelligence
- Electrical and Electronic Engineering