DIGIT: A Novel Design for a Low-Cost Compact High-Resolution Tactile Sensor With Application to In-Hand Manipulation

Despite decades of research, general purpose in-hand manipulation remains one of the unsolved challenges of robotics. One of the contributing factors that limit current robotic manipulation systems is the difficulty of precisely sensing contact forces - sensing and reasoning about contact forces are...

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Vydané v:	IEEE robotics and automation letters Ročník 5; číslo 3; s. 3838 - 3845
Hlavní autori:	Lambeta, Mike, Chou, Po-Wei, Tian, Stephen, Yang, Brian, Maloon, Benjamin, Most, Victoria Rose, Stroud, Dave, Santos, Raymond, Byagowi, Ahmad, Kammerer, Gregg, Jayaraman, Dinesh, Calandra, Roberto
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 01.07.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Artificial neural networks Automation Cameras Contact force deep learning in robotics and automation Design improvements End effectors force and tactile sensing Form factors Hand (anatomy) High resolution learning and adaptive systems Low cost Manufacturing engineering Miniaturization Perception for grasping and manipulation Reliability Robotics Sensors Tactile sensors Tactile sensors (robotics) Task analysis
ISSN:	2377-3766, 2377-3766
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Abstract	Despite decades of research, general purpose in-hand manipulation remains one of the unsolved challenges of robotics. One of the contributing factors that limit current robotic manipulation systems is the difficulty of precisely sensing contact forces - sensing and reasoning about contact forces are crucial to accurately control interactions with the environment. As a step towards enabling better robotic manipulation, we introduce DIGIT, an inexpensive, compact, and high-resolution tactile sensor geared towards in-hand manipulation. DIGIT improves upon past vision-based tactile sensors by miniaturizing the form factor to be mountable on multi-fingered hands, and by providing several design improvements that result in an easier, more repeatable manufacturing process, and enhanced reliability. We demonstrate the capabilities of the DIGIT sensor by training deep neural network model-based controllers to manipulate glass marbles in-hand with a multi-finger robotic hand. To provide the robotic community access to reliable and low-cost tactile sensors, we open-source the DIGIT design at www.digit.ml .
AbstractList	Despite decades of research, general purpose in-hand manipulation remains one of the unsolved challenges of robotics. One of the contributing factors that limit current robotic manipulation systems is the difficulty of precisely sensing contact forces – sensing and reasoning about contact forces are crucial to accurately control interactions with the environment. As a step towards enabling better robotic manipulation, we introduce DIGIT, an inexpensive, compact, and high-resolution tactile sensor geared towards in-hand manipulation. DIGIT improves upon past vision-based tactile sensors by miniaturizing the form factor to be mountable on multi-fingered hands, and by providing several design improvements that result in an easier, more repeatable manufacturing process, and enhanced reliability. We demonstrate the capabilities of the DIGIT sensor by training deep neural network model-based controllers to manipulate glass marbles in-hand with a multi-finger robotic hand. To provide the robotic community access to reliable and low-cost tactile sensors, we open-source the DIGIT design at www.digit.ml .
Author	Jayaraman, Dinesh Maloon, Benjamin Byagowi, Ahmad Lambeta, Mike Stroud, Dave Calandra, Roberto Kammerer, Gregg Most, Victoria Rose Chou, Po-Wei Tian, Stephen Yang, Brian Santos, Raymond
Author_xml	– sequence: 1 givenname: Mike surname: Lambeta fullname: Lambeta, Mike email: lambetam@fb.com organization: Facebook, Menlo Park, CA, USA – sequence: 2 givenname: Po-Wei surname: Chou fullname: Chou, Po-Wei email: poweic.andrew@gmail.com organization: Facebook, Menlo Park, CA, USA – sequence: 3 givenname: Stephen orcidid: 0000-0003-3148-5541 surname: Tian fullname: Tian, Stephen email: stephentian@berkeley.edu organization: Facebook, Menlo Park, CA, USA – sequence: 4 givenname: Brian orcidid: 0000-0001-8784-1459 surname: Yang fullname: Yang, Brian email: brianhyang@berkeley.edu organization: Facebook, Menlo Park, CA, USA – sequence: 5 givenname: Benjamin surname: Maloon fullname: Maloon, Benjamin email: Benjamin.maloon@fb.com organization: Facebook, Menlo Park, CA, USA – sequence: 6 givenname: Victoria Rose surname: Most fullname: Most, Victoria Rose email: victoriamost@fb.com organization: Facebook, Menlo Park, CA, USA – sequence: 7 givenname: Dave surname: Stroud fullname: Stroud, Dave email: dstroud@fb.com organization: Facebook, Menlo Park, CA, USA – sequence: 8 givenname: Raymond surname: Santos fullname: Santos, Raymond email: raysantos@fb.com organization: Facebook, Menlo Park, CA, USA – sequence: 9 givenname: Ahmad surname: Byagowi fullname: Byagowi, Ahmad email: abyagowi@fb.com organization: Facebook, Menlo Park, CA, USA – sequence: 10 givenname: Gregg surname: Kammerer fullname: Kammerer, Gregg email: GreggK@FB.com organization: Facebook, Menlo Park, CA, USA – sequence: 11 givenname: Dinesh orcidid: 0000-0002-6888-3095 surname: Jayaraman fullname: Jayaraman, Dinesh email: dinesh.jayaraman123@gmail.com organization: Facebook, Menlo Park, CA, USA – sequence: 12 givenname: Roberto orcidid: 0000-0001-9430-8433 surname: Calandra fullname: Calandra, Roberto email: rcalandra@fb.com organization: Facebook, Menlo Park, CA, USA
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Snippet	Despite decades of research, general purpose in-hand manipulation remains one of the unsolved challenges of robotics. One of the contributing factors that...
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SubjectTerms	Artificial neural networks Automation Cameras Contact force deep learning in robotics and automation Design improvements End effectors force and tactile sensing Form factors Hand (anatomy) High resolution learning and adaptive systems Low cost Manufacturing engineering Miniaturization Perception for grasping and manipulation Reliability Robotics Sensors Tactile sensors Tactile sensors (robotics) Task analysis
Title	DIGIT: A Novel Design for a Low-Cost Compact High-Resolution Tactile Sensor With Application to In-Hand Manipulation
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