Belief-Space Planning Using Learned Models with Application to Underactuated Hands

Andrew Kimmel*, Avishai Sintov, Juntao Tan, Bowen Wen, Abdeslam Boularias, Kostas E. Bekris

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations


Acquiring a precise model is a challenging task for many important robotic tasks and systems - including in-hand manipulation using underactuated, adaptive hands. Learning stochastic, data-driven models is a promising alternative as they provide not only a way to propagate forward the system dynamics, but also express the uncertainty present in the collected data. Therefore, such models enable planning in the space of state distributions, i.e., in the belief space. This paper proposes a planning framework for solving Non-Observable Markov Decision Process (NOMDP) problems which employs learned stochastic models, expressing a distribution of states as a set of particles. The integration achieves anytime behavior in terms of returning paths of increasing quality under constraints for the probability of success to achieve a goal. The focus of this effort is on pushing the efficiency of the overall methodology despite the notorious computational hardness of belief-space planning. Experiments show that the proposed framework enables reaching a desired goal with higher success rate compared to alternatives in simple benchmarks. This work also provides an application to the motivating domain of in-hand manipulation with underactuated, adaptive hands, both in the case of physically-simulated experiments as well as demonstrations with a real hand.

Original languageEnglish
Title of host publicationRobotics Research - The 19th International Symposium ISRR
EditorsTamim Asfour, Eiichi Yoshida, Jaeheung Park, Henrik Christensen, Oussama Khatib
PublisherSpringer Nature
Number of pages18
ISBN (Print)9783030954581
StatePublished - 2022
Externally publishedYes
Event17th International Symposium of Robotics Research, ISRR 2019 - Hanoi, Viet Nam
Duration: 6 Oct 201910 Oct 2019

Publication series

NameSpringer Proceedings in Advanced Robotics
Volume20 SPAR
ISSN (Print)2511-1256
ISSN (Electronic)2511-1264


Conference17th International Symposium of Robotics Research, ISRR 2019
Country/TerritoryViet Nam


FundersFunder number
National Science Foundation1723869, 1734492


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