DocumentCode :
3507883
Title :
Robotic object grasping in context of human grasping and manipulation
Author :
Dzitac, Pavel ; Md Mazid, Abdul
Author_Institution :
Sch. of Eng. & Technol., Central Queensland Univ. Australia, Rockhampton, QLD, Australia
fYear :
2013
fDate :
12-15 Nov. 2013
Firstpage :
201
Lastpage :
206
Abstract :
This paper presents experimental and deductive findings that shed new light on grasp force estimation, which improves robot´s chances to grasp and manipulate the object close to optimum conditions on the first attempt, which in turn improves robot´s object manipulation dexterity. This paper proposes that object slippage detection in the human hand is not detected based purely on micro-vibrations sensed by the human skin during incipient slippage but also on load sensing at each finger and movement of fingers relative to each other while holding an object.
Keywords :
dexterous manipulators; force sensors; industrial manipulators; skin; finger movement; force sensors; grasp force estimation; human grasping; human manipulation; industrial robots; load sensing; object slippage detection; robot object manipulation dexterity; robotic object grasping; Force; Grasping; Predictive models; Robot sensing systems; Thumb; grasp force; human grasping; robotic grasping; slippage;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics, Automation and Mechatronics (RAM), 2013 6th IEEE Conference on
Conference_Location :
Manila
ISSN :
2158-2181
Print_ISBN :
978-1-4799-1198-1
Type :
conf
DOI :
10.1109/RAM.2013.6758584
Filename :
6758584
Link To Document :
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