Robotic object grasping in context of human grasping and manipulation

Pavel Dzitac; Abdul Md Mazid

doi:10.1109/RAM.2013.6758584

Robotic object grasping in context of human grasping and manipulation

Pavel Dzitac, Abdul Md Mazid

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

1 Citation (Scopus)

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.

Original language	English
Title of host publication	Proceedings of the 2013 6th IEEE Conference on Robotics, Automation and Mechatronics, RAM 2013
Place of Publication	Piscataway, NJ
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	201-206
Number of pages	6
ISBN (Electronic)	9781479911981
ISBN (Print)	9781479911998, 9781479912018
DOIs	https://doi.org/10.1109/RAM.2013.6758584
Publication status	Published - 2013
Externally published	Yes
Event	2013 6th IEEE Conference on Robotics, Automation and Mechatronics, RAM 2013 - Manila, Philippines Duration: 12 Nov 2013 → 15 Nov 2013

Other

Other	2013 6th IEEE Conference on Robotics, Automation and Mechatronics, RAM 2013
Country/Territory	Philippines
City	Manila
Period	12/11/13 → 15/11/13

Keywords

slippage
robotic grasping
grasp force
human grasping

Access to Document

10.1109/RAM.2013.6758584

Cite this

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title = "Robotic object grasping in context of human grasping and manipulation",

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 = "slippage, robotic grasping, grasp force, human grasping",

author = "Pavel Dzitac and \{Md Mazid\}, Abdul",

year = "2013",

doi = "10.1109/RAM.2013.6758584",

language = "English",

isbn = "9781479911998",

pages = "201--206",

booktitle = "Proceedings of the 2013 6th IEEE Conference on Robotics, Automation and Mechatronics, RAM 2013",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

note = "2013 6th IEEE Conference on Robotics, Automation and Mechatronics, RAM 2013 ; Conference date: 12-11-2013 Through 15-11-2013",

}

Dzitac, P & Md Mazid, A 2013, Robotic object grasping in context of human grasping and manipulation. in Proceedings of the 2013 6th IEEE Conference on Robotics, Automation and Mechatronics, RAM 2013., 6758584, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, pp. 201-206, 2013 6th IEEE Conference on Robotics, Automation and Mechatronics, RAM 2013, Manila, Philippines, 12/11/13. https://doi.org/10.1109/RAM.2013.6758584

Robotic object grasping in context of human grasping and manipulation. / Dzitac, Pavel; Md Mazid, Abdul.
Proceedings of the 2013 6th IEEE Conference on Robotics, Automation and Mechatronics, RAM 2013. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2013. p. 201-206 6758584.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

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AU - Md Mazid, Abdul

PY - 2013

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N2 - 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.

AB - 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.

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KW - robotic grasping

KW - grasp force

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DO - 10.1109/RAM.2013.6758584

M3 - Conference proceeding contribution

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BT - Proceedings of the 2013 6th IEEE Conference on Robotics, Automation and Mechatronics, RAM 2013

PB - Institute of Electrical and Electronics Engineers (IEEE)

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T2 - 2013 6th IEEE Conference on Robotics, Automation and Mechatronics, RAM 2013

Y2 - 12 November 2013 through 15 November 2013

ER -

Robotic object grasping in context of human grasping and manipulation

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