Optimizing Pick and Place Operations in a Simulated Work Cell for Deformable 3D Objects

Publikation: Kapitel i bog/rapport/konference-proceedingKonferencebidrag i proceedingsForskningpeer review

Abstract

This paper presents a simulation framework for using machine learning techniques to determine robust robotic motions for handling deformable objects. The main focus is on applications in the meat sector, which mainly handle three-dimensional objects. In order to optimize the robotic handling, the robot motions have been parametrized in terms of grasp points, robot trajectory and robot speed. The motions are evaluated based on a dynamic simulation environment for robotic control of deformable objects. The evaluation indicates certain parameter setups, which produce robust motions in the simulated environment, and based on a visual analysis indicate satisfactory solutions for a real world system.

OriginalsprogEngelsk
TitelIntelligent Robotics and Applications
RedaktørerHonghai Liu, Naoyuki Kubota, Xiangyang Zhu, Rüdiger Dillmann, Dalin Zhou
ForlagSpringer
Publikationsdato2015
Sider431-444
ISBN (Trykt)978-3-319-22875-4
ISBN (Elektronisk)978-3-319-22876-1
DOI
StatusUdgivet - 2015
Begivenhed8th International Conference on Intelligent Robotics and Applications - Portsmouth, Storbritannien
Varighed: 24. aug. 201527. aug. 2015

Konference

Konference8th International Conference on Intelligent Robotics and Applications
Land/OmrådeStorbritannien
ByPortsmouth
Periode24/08/201527/08/2015
NavnLecture Notes in Computer Science
Vol/bind9245
ISSN0302-9743

Fingeraftryk

Dyk ned i forskningsemnerne om 'Optimizing Pick and Place Operations in a Simulated Work Cell for Deformable 3D Objects'. Sammen danner de et unikt fingeraftryk.

Citationsformater