In-Hand Pose Refinement Based on Contact Point Information

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Abstract

This paper presents a method for in-hand pose refinement using point pair features and robust estimation. The algorithm assumes that an initial pose distribution is available, and uses this for an initial guess of the correspondences between source and target data. The data needed for the algorithm is points and surface normal vectors that can be estimated from force-torque data; thus, tactile sensor arrays are not needed. The method is demonstrated on the in-hand pose estimation of an object in an articulated five finger hand.

OriginalsprogEngelsk
TitelAdvances in Service and Industrial Robotics - RAAD 2023
RedaktørerTadej Petrič, Aleš Ude, Leon Žlajpah
ForlagSpringer Science+Business Media
Publikationsdato2023
Sider29-36
ISBN (Trykt)9783031326059
DOI
StatusUdgivet - 2023
Begivenhed32nd International Conference on Robotics in Alpe-Adria-Danube Region, RAAD 2023 - Bled, Slovenien
Varighed: 14. jun. 202316. jun. 2023

Konference

Konference32nd International Conference on Robotics in Alpe-Adria-Danube Region, RAAD 2023
Land/OmrådeSlovenien
ByBled
Periode14/06/202316/06/2023
NavnMechanisms and Machine Science
Vol/bind135 MMS
ISSN2211-0984

Bibliografisk note

Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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