Decentralized parameter estimation and observation for cooperative mobile manipulation of an unknown load using noisy measurements

Antonio Franchi, Antonio Petitti, Alessandro Rizzo

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

22 Citations (Scopus)

Abstract

In this paper, a distributed approach for the estimation of kinematic and inertial parameters of an unknown rigid body is presented. The body is manipulated by a pool of ground mobile manipulators. Each robot retrieves a noisy measurement of its velocity and the contact forces applied to the body. Kinematics and dynamics arguments are used to distributively estimate the relative positions of the contact points. Subsequently, distributed estimation filters and nonlinear observers are used to estimate the body mass, the relative position between its geometric center and its center of mass, and its moment of inertia. The manipulation strategy is functional to the estimation process, and is suitably designed to satisfy nonlinear observability conditions that are necessary for the success of the estimation. Numerical results corroborate our theoretical findings.

Original languageEnglish
Title of host publication2015 IEEE International Conference on Robotics and Automation (ICRA)
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages5517-5522
Number of pages6
ISBN (Electronic)978-1-4799-6923-4
ISBN (Print)978-1-4799-6923-4
DOIs
Publication statusPublished - 29 Jun 2015
Externally publishedYes
Event2015 IEEE International Conference on Robotics and Automation, ICRA 2015 - Seattle, United States
Duration: 26 May 201530 May 2015

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation (ICRA)
PublisherIEEE
Volume2015
ISSN (Print)1050-4729

Conference

Conference2015 IEEE International Conference on Robotics and Automation, ICRA 2015
Abbreviated titleICRA
CountryUnited States
CitySeattle
Period26/05/1530/05/15

Fingerprint Dive into the research topics of 'Decentralized parameter estimation and observation for cooperative mobile manipulation of an unknown load using noisy measurements'. Together they form a unique fingerprint.

Cite this