Benchmark for Bimanual Robotic Manipulation of Semi-Deformable Objects

被引：25

作者：

Chatzilygeroudis, Konstantinos ^{[1
]}

Fichera, Bernardo ^{[1
]}

Lauzana, Ilaria ^{[1
]}

Bu, Fanjun ^{[1
,2
]}

Yao, Kunpeng ^{[1
]}

Khadivar, Farshad ^{[1
]}

Billard, Aude ^{[1
]}

机构：

[1] Ecole Polytech Fed Lausanne, Learning Algorithms & Syst Lab, CH-1015 Lausanne, Switzerland

[2] Johns Hopkins Univ, Baltimore, MD 21218 USA

来源：

IEEE ROBOTICS AND AUTOMATION LETTERS | 2020年 / 5卷 / 02期

基金：

欧洲研究理事会;

关键词：

Performance evaluation and benchmarking; dual arm manipulation; model learning for control; dexterous manipulation; PEG-IN-HOLE; COORDINATION;

D O I：

10.1109/LRA.2020.2972837

中图分类号：

TP24 [机器人技术];

学科分类号：

080202 ; 1405 ;

摘要：

We propose a new benchmarking protocol to evaluate algorithms for bimanual robotic manipulation semi-deformable objects. The benchmark is inspired from two real-world applications: (a) watchmaking craftsmanship, and (b) belt assembly in automobile engines. We provide two setups that try to highlight the following challenges: (a) manipulating objects via a tool, (b) placing irregularly shaped objects in the correct groove, (c) handling semi-deformable objects, and (d) bimanual coordination. We provide CAD drawings of the task pieces that can be easily 3D printed to ensure ease of reproduction, and detailed description of tasks and protocol for successful reproduction, as well as meaningful metrics for comparison. We propose four categories of submission in an attempt to make the benchmark accessible to a wide range of related fields spanning from adaptive control, motion planning to learning the tasks through trial-and-error learning.

引用

页码：2443 / 2450

页数：8

共 36 条

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