Robust, Occlusion-aware Pose Estimation for Objects Grasped by Adaptive Hands

Bowen Wen, Chaitanya Mitash, Sruthi Soorian, Andrew Kimmel, Avishai Sintov, Kostas E. Bekris

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Many manipulation tasks, such as placement or within-hand manipulation, require the object's pose relative to a robot hand. The task is difficult when the hand significantly occludes the object. It is especially hard for adaptive hands, for which it is not easy to detect the finger's configuration. In addition, RGB-only approaches face issues with texture-less objects or when the hand and the object look similar. This paper presents a depth-based framework, which aims for robust pose estimation and short response times. The approach detects the adaptive hand's state via efficient parallel search given the highest overlap between the hand's model and the point cloud. The hand's point cloud is pruned and robust global registration is performed to generate object pose hypotheses, which are clustered. False hypotheses are pruned via physical reasoning. The remaining poses' quality is evaluated given agreement with observed data. Extensive evaluation on synthetic and real data demonstrates the accuracy and computational efficiency of the framework when applied on challenging, highly-occluded scenarios for different object types. An ablation study identifies how the framework's components help in performance. This work also provides a dataset for in-hand 6D object pose estimation. Code and dataset are available at: https://github.com/wenbowen123/icra20-hand-object-pose.

Original languageEnglish (US)
Title of host publication2020 IEEE International Conference on Robotics and Automation, ICRA 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6210-6217
Number of pages8
ISBN (Electronic)9781728173955
DOIs
StatePublished - May 2020
Externally publishedYes
Event2020 IEEE International Conference on Robotics and Automation, ICRA 2020 - Paris, France
Duration: May 31 2020Aug 31 2020

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729

Conference

Conference2020 IEEE International Conference on Robotics and Automation, ICRA 2020
Country/TerritoryFrance
CityParis
Period5/31/208/31/20

All Science Journal Classification (ASJC) codes

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Robust, Occlusion-aware Pose Estimation for Objects Grasped by Adaptive Hands'. Together they form a unique fingerprint.

Cite this