Understanding human–robot interaction forces: a new mechanical solution

Abstract Nowadays, robots hold crucial roles in an increasing number of different fields, highlighting an ongoing transition to ever-closer collaboration between humans and machines. In this context, this new technological era has brought out safety issues and, consequently, robots need to be monito...
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Autor*in:	Pippo, Irene [verfasserIn] Albanese, Giulia Aurora [verfasserIn] Zenzeri, Jacopo [verfasserIn] Torazza, Diego [verfasserIn] Berselli, Giovanni [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2024

Schlagwörter:	Human–robot interaction CAD design Mechanical design Interaction forces Virtual prototyping

Anmerkung:	© The Author(s) 2024

Übergeordnetes Werk:	Enthalten in: International journal on interactive design and manufacturing - Springer Paris, 2007, 18(2024), 7 vom: 07. März, Seite 4765-4774
Übergeordnetes Werk:	volume:18 ; year:2024 ; number:7 ; day:07 ; month:03 ; pages:4765-4774

Links:	Volltext

DOI / URN:	10.1007/s12008-024-01735-z

Katalog-ID:	SPR057291241

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520			\|a Abstract Nowadays, robots hold crucial roles in an increasing number of different fields, highlighting an ongoing transition to ever-closer collaboration between humans and machines. In this context, this new technological era has brought out safety issues and, consequently, robots need to be monitored with an appropriate control architecture and human–machine interaction forces should be correctly estimated. For this purpose, friction, inertia, external perturbation, and the intrinsic dynamic of the robots should be monitored. This specific work starts from the need to monitor human–robot interaction forces to ensure safety for users. A successful case study concerning the integration of additional sensors on a wrist robot that directly interacts with humans is shown. Its limits have been the inability to directly measure forces applied by users and the impossibility to know accurately the end-effector position. Firstly, introducing a force/torque sensor, the detection of the forces applied by the user to the robot has been enabled. The user’s force data have been used to measure force dissipation and, together with the smoothness of operation, to compare three different embeddable mechanisms. Moreover, the integration of a linear encoder allowed measuring the instantaneous end-effector position on a non-actuated linear guideway, consequently knowing the motor torque value and the force applied by the robot to the user. This has been compared to the interaction force estimated from the motor torques without the linear sensor. The error assessed between the force measured with the encoder and estimated without it is about 12.9%. These results demonstrate the importance of this new embedded system to detect human–machine interaction forces in an accurate way and prevent safety issues.
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allfields	10.1007/s12008-024-01735-z doi (DE-627)SPR057291241 (SPR)s12008-024-01735-z-e DE-627 ger DE-627 rakwb eng 690 VZ Pippo, Irene verfasserin aut Understanding human–robot interaction forces: a new mechanical solution 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 Abstract Nowadays, robots hold crucial roles in an increasing number of different fields, highlighting an ongoing transition to ever-closer collaboration between humans and machines. In this context, this new technological era has brought out safety issues and, consequently, robots need to be monitored with an appropriate control architecture and human–machine interaction forces should be correctly estimated. For this purpose, friction, inertia, external perturbation, and the intrinsic dynamic of the robots should be monitored. This specific work starts from the need to monitor human–robot interaction forces to ensure safety for users. A successful case study concerning the integration of additional sensors on a wrist robot that directly interacts with humans is shown. Its limits have been the inability to directly measure forces applied by users and the impossibility to know accurately the end-effector position. Firstly, introducing a force/torque sensor, the detection of the forces applied by the user to the robot has been enabled. The user’s force data have been used to measure force dissipation and, together with the smoothness of operation, to compare three different embeddable mechanisms. Moreover, the integration of a linear encoder allowed measuring the instantaneous end-effector position on a non-actuated linear guideway, consequently knowing the motor torque value and the force applied by the robot to the user. This has been compared to the interaction force estimated from the motor torques without the linear sensor. The error assessed between the force measured with the encoder and estimated without it is about 12.9%. These results demonstrate the importance of this new embedded system to detect human–machine interaction forces in an accurate way and prevent safety issues. Human–robot interaction (dpeaa)DE-He213 CAD design (dpeaa)DE-He213 Mechanical design (dpeaa)DE-He213 Interaction forces (dpeaa)DE-He213 Virtual prototyping (dpeaa)DE-He213 Albanese, Giulia Aurora verfasserin aut Zenzeri, Jacopo verfasserin aut Torazza, Diego verfasserin aut Berselli, Giovanni verfasserin aut Enthalten in International journal on interactive design and manufacturing Springer Paris, 2007 18(2024), 7 vom: 07. März, Seite 4765-4774 (DE-627)546503195 (DE-600)2390733-2 1955-2505 nnns volume:18 year:2024 number:7 day:07 month:03 pages:4765-4774 https://dx.doi.org/10.1007/s12008-024-01735-z X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 18 2024 7 07 03 4765-4774
spelling	10.1007/s12008-024-01735-z doi (DE-627)SPR057291241 (SPR)s12008-024-01735-z-e DE-627 ger DE-627 rakwb eng 690 VZ Pippo, Irene verfasserin aut Understanding human–robot interaction forces: a new mechanical solution 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 Abstract Nowadays, robots hold crucial roles in an increasing number of different fields, highlighting an ongoing transition to ever-closer collaboration between humans and machines. In this context, this new technological era has brought out safety issues and, consequently, robots need to be monitored with an appropriate control architecture and human–machine interaction forces should be correctly estimated. For this purpose, friction, inertia, external perturbation, and the intrinsic dynamic of the robots should be monitored. This specific work starts from the need to monitor human–robot interaction forces to ensure safety for users. A successful case study concerning the integration of additional sensors on a wrist robot that directly interacts with humans is shown. Its limits have been the inability to directly measure forces applied by users and the impossibility to know accurately the end-effector position. Firstly, introducing a force/torque sensor, the detection of the forces applied by the user to the robot has been enabled. The user’s force data have been used to measure force dissipation and, together with the smoothness of operation, to compare three different embeddable mechanisms. Moreover, the integration of a linear encoder allowed measuring the instantaneous end-effector position on a non-actuated linear guideway, consequently knowing the motor torque value and the force applied by the robot to the user. This has been compared to the interaction force estimated from the motor torques without the linear sensor. The error assessed between the force measured with the encoder and estimated without it is about 12.9%. These results demonstrate the importance of this new embedded system to detect human–machine interaction forces in an accurate way and prevent safety issues. Human–robot interaction (dpeaa)DE-He213 CAD design (dpeaa)DE-He213 Mechanical design (dpeaa)DE-He213 Interaction forces (dpeaa)DE-He213 Virtual prototyping (dpeaa)DE-He213 Albanese, Giulia Aurora verfasserin aut Zenzeri, Jacopo verfasserin aut Torazza, Diego verfasserin aut Berselli, Giovanni verfasserin aut Enthalten in International journal on interactive design and manufacturing Springer Paris, 2007 18(2024), 7 vom: 07. März, Seite 4765-4774 (DE-627)546503195 (DE-600)2390733-2 1955-2505 nnns volume:18 year:2024 number:7 day:07 month:03 pages:4765-4774 https://dx.doi.org/10.1007/s12008-024-01735-z X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 18 2024 7 07 03 4765-4774
allfields_unstemmed	10.1007/s12008-024-01735-z doi (DE-627)SPR057291241 (SPR)s12008-024-01735-z-e DE-627 ger DE-627 rakwb eng 690 VZ Pippo, Irene verfasserin aut Understanding human–robot interaction forces: a new mechanical solution 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 Abstract Nowadays, robots hold crucial roles in an increasing number of different fields, highlighting an ongoing transition to ever-closer collaboration between humans and machines. In this context, this new technological era has brought out safety issues and, consequently, robots need to be monitored with an appropriate control architecture and human–machine interaction forces should be correctly estimated. For this purpose, friction, inertia, external perturbation, and the intrinsic dynamic of the robots should be monitored. This specific work starts from the need to monitor human–robot interaction forces to ensure safety for users. A successful case study concerning the integration of additional sensors on a wrist robot that directly interacts with humans is shown. Its limits have been the inability to directly measure forces applied by users and the impossibility to know accurately the end-effector position. Firstly, introducing a force/torque sensor, the detection of the forces applied by the user to the robot has been enabled. The user’s force data have been used to measure force dissipation and, together with the smoothness of operation, to compare three different embeddable mechanisms. Moreover, the integration of a linear encoder allowed measuring the instantaneous end-effector position on a non-actuated linear guideway, consequently knowing the motor torque value and the force applied by the robot to the user. This has been compared to the interaction force estimated from the motor torques without the linear sensor. The error assessed between the force measured with the encoder and estimated without it is about 12.9%. These results demonstrate the importance of this new embedded system to detect human–machine interaction forces in an accurate way and prevent safety issues. Human–robot interaction (dpeaa)DE-He213 CAD design (dpeaa)DE-He213 Mechanical design (dpeaa)DE-He213 Interaction forces (dpeaa)DE-He213 Virtual prototyping (dpeaa)DE-He213 Albanese, Giulia Aurora verfasserin aut Zenzeri, Jacopo verfasserin aut Torazza, Diego verfasserin aut Berselli, Giovanni verfasserin aut Enthalten in International journal on interactive design and manufacturing Springer Paris, 2007 18(2024), 7 vom: 07. März, Seite 4765-4774 (DE-627)546503195 (DE-600)2390733-2 1955-2505 nnns volume:18 year:2024 number:7 day:07 month:03 pages:4765-4774 https://dx.doi.org/10.1007/s12008-024-01735-z X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 18 2024 7 07 03 4765-4774
allfieldsGer	10.1007/s12008-024-01735-z doi (DE-627)SPR057291241 (SPR)s12008-024-01735-z-e DE-627 ger DE-627 rakwb eng 690 VZ Pippo, Irene verfasserin aut Understanding human–robot interaction forces: a new mechanical solution 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 Abstract Nowadays, robots hold crucial roles in an increasing number of different fields, highlighting an ongoing transition to ever-closer collaboration between humans and machines. In this context, this new technological era has brought out safety issues and, consequently, robots need to be monitored with an appropriate control architecture and human–machine interaction forces should be correctly estimated. For this purpose, friction, inertia, external perturbation, and the intrinsic dynamic of the robots should be monitored. This specific work starts from the need to monitor human–robot interaction forces to ensure safety for users. A successful case study concerning the integration of additional sensors on a wrist robot that directly interacts with humans is shown. Its limits have been the inability to directly measure forces applied by users and the impossibility to know accurately the end-effector position. Firstly, introducing a force/torque sensor, the detection of the forces applied by the user to the robot has been enabled. The user’s force data have been used to measure force dissipation and, together with the smoothness of operation, to compare three different embeddable mechanisms. Moreover, the integration of a linear encoder allowed measuring the instantaneous end-effector position on a non-actuated linear guideway, consequently knowing the motor torque value and the force applied by the robot to the user. This has been compared to the interaction force estimated from the motor torques without the linear sensor. The error assessed between the force measured with the encoder and estimated without it is about 12.9%. These results demonstrate the importance of this new embedded system to detect human–machine interaction forces in an accurate way and prevent safety issues. Human–robot interaction (dpeaa)DE-He213 CAD design (dpeaa)DE-He213 Mechanical design (dpeaa)DE-He213 Interaction forces (dpeaa)DE-He213 Virtual prototyping (dpeaa)DE-He213 Albanese, Giulia Aurora verfasserin aut Zenzeri, Jacopo verfasserin aut Torazza, Diego verfasserin aut Berselli, Giovanni verfasserin aut Enthalten in International journal on interactive design and manufacturing Springer Paris, 2007 18(2024), 7 vom: 07. März, Seite 4765-4774 (DE-627)546503195 (DE-600)2390733-2 1955-2505 nnns volume:18 year:2024 number:7 day:07 month:03 pages:4765-4774 https://dx.doi.org/10.1007/s12008-024-01735-z X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 18 2024 7 07 03 4765-4774
allfieldsSound	10.1007/s12008-024-01735-z doi (DE-627)SPR057291241 (SPR)s12008-024-01735-z-e DE-627 ger DE-627 rakwb eng 690 VZ Pippo, Irene verfasserin aut Understanding human–robot interaction forces: a new mechanical solution 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2024 Abstract Nowadays, robots hold crucial roles in an increasing number of different fields, highlighting an ongoing transition to ever-closer collaboration between humans and machines. In this context, this new technological era has brought out safety issues and, consequently, robots need to be monitored with an appropriate control architecture and human–machine interaction forces should be correctly estimated. For this purpose, friction, inertia, external perturbation, and the intrinsic dynamic of the robots should be monitored. This specific work starts from the need to monitor human–robot interaction forces to ensure safety for users. A successful case study concerning the integration of additional sensors on a wrist robot that directly interacts with humans is shown. Its limits have been the inability to directly measure forces applied by users and the impossibility to know accurately the end-effector position. Firstly, introducing a force/torque sensor, the detection of the forces applied by the user to the robot has been enabled. The user’s force data have been used to measure force dissipation and, together with the smoothness of operation, to compare three different embeddable mechanisms. Moreover, the integration of a linear encoder allowed measuring the instantaneous end-effector position on a non-actuated linear guideway, consequently knowing the motor torque value and the force applied by the robot to the user. This has been compared to the interaction force estimated from the motor torques without the linear sensor. The error assessed between the force measured with the encoder and estimated without it is about 12.9%. These results demonstrate the importance of this new embedded system to detect human–machine interaction forces in an accurate way and prevent safety issues. Human–robot interaction (dpeaa)DE-He213 CAD design (dpeaa)DE-He213 Mechanical design (dpeaa)DE-He213 Interaction forces (dpeaa)DE-He213 Virtual prototyping (dpeaa)DE-He213 Albanese, Giulia Aurora verfasserin aut Zenzeri, Jacopo verfasserin aut Torazza, Diego verfasserin aut Berselli, Giovanni verfasserin aut Enthalten in International journal on interactive design and manufacturing Springer Paris, 2007 18(2024), 7 vom: 07. März, Seite 4765-4774 (DE-627)546503195 (DE-600)2390733-2 1955-2505 nnns volume:18 year:2024 number:7 day:07 month:03 pages:4765-4774 https://dx.doi.org/10.1007/s12008-024-01735-z X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 18 2024 7 07 03 4765-4774
language	English
source	Enthalten in International journal on interactive design and manufacturing 18(2024), 7 vom: 07. März, Seite 4765-4774 volume:18 year:2024 number:7 day:07 month:03 pages:4765-4774
sourceStr	Enthalten in International journal on interactive design and manufacturing 18(2024), 7 vom: 07. März, Seite 4765-4774 volume:18 year:2024 number:7 day:07 month:03 pages:4765-4774
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Human–robot interaction CAD design Mechanical design Interaction forces Virtual prototyping
dewey-raw	690
isfreeaccess_bool	true
container_title	International journal on interactive design and manufacturing
authorswithroles_txt_mv	Pippo, Irene @@aut@@ Albanese, Giulia Aurora @@aut@@ Zenzeri, Jacopo @@aut@@ Torazza, Diego @@aut@@ Berselli, Giovanni @@aut@@
publishDateDaySort_date	2024-03-07T00:00:00Z
hierarchy_top_id	546503195
dewey-sort	3690
id	SPR057291241
language_de	englisch
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author	Pippo, Irene
spellingShingle	Pippo, Irene ddc 690 misc Human–robot interaction misc CAD design misc Mechanical design misc Interaction forces misc Virtual prototyping Understanding human–robot interaction forces: a new mechanical solution
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topic_title	690 VZ Understanding human–robot interaction forces: a new mechanical solution Human–robot interaction (dpeaa)DE-He213 CAD design (dpeaa)DE-He213 Mechanical design (dpeaa)DE-He213 Interaction forces (dpeaa)DE-He213 Virtual prototyping (dpeaa)DE-He213
topic	ddc 690 misc Human–robot interaction misc CAD design misc Mechanical design misc Interaction forces misc Virtual prototyping
topic_unstemmed	ddc 690 misc Human–robot interaction misc CAD design misc Mechanical design misc Interaction forces misc Virtual prototyping
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title	Understanding human–robot interaction forces: a new mechanical solution
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title_full	Understanding human–robot interaction forces: a new mechanical solution
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author_browse	Pippo, Irene Albanese, Giulia Aurora Zenzeri, Jacopo Torazza, Diego Berselli, Giovanni
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title_sort	understanding human–robot interaction forces: a new mechanical solution
title_auth	Understanding human–robot interaction forces: a new mechanical solution
abstract	Abstract Nowadays, robots hold crucial roles in an increasing number of different fields, highlighting an ongoing transition to ever-closer collaboration between humans and machines. In this context, this new technological era has brought out safety issues and, consequently, robots need to be monitored with an appropriate control architecture and human–machine interaction forces should be correctly estimated. For this purpose, friction, inertia, external perturbation, and the intrinsic dynamic of the robots should be monitored. This specific work starts from the need to monitor human–robot interaction forces to ensure safety for users. A successful case study concerning the integration of additional sensors on a wrist robot that directly interacts with humans is shown. Its limits have been the inability to directly measure forces applied by users and the impossibility to know accurately the end-effector position. Firstly, introducing a force/torque sensor, the detection of the forces applied by the user to the robot has been enabled. The user’s force data have been used to measure force dissipation and, together with the smoothness of operation, to compare three different embeddable mechanisms. Moreover, the integration of a linear encoder allowed measuring the instantaneous end-effector position on a non-actuated linear guideway, consequently knowing the motor torque value and the force applied by the robot to the user. This has been compared to the interaction force estimated from the motor torques without the linear sensor. The error assessed between the force measured with the encoder and estimated without it is about 12.9%. These results demonstrate the importance of this new embedded system to detect human–machine interaction forces in an accurate way and prevent safety issues. © The Author(s) 2024
abstractGer	Abstract Nowadays, robots hold crucial roles in an increasing number of different fields, highlighting an ongoing transition to ever-closer collaboration between humans and machines. In this context, this new technological era has brought out safety issues and, consequently, robots need to be monitored with an appropriate control architecture and human–machine interaction forces should be correctly estimated. For this purpose, friction, inertia, external perturbation, and the intrinsic dynamic of the robots should be monitored. This specific work starts from the need to monitor human–robot interaction forces to ensure safety for users. A successful case study concerning the integration of additional sensors on a wrist robot that directly interacts with humans is shown. Its limits have been the inability to directly measure forces applied by users and the impossibility to know accurately the end-effector position. Firstly, introducing a force/torque sensor, the detection of the forces applied by the user to the robot has been enabled. The user’s force data have been used to measure force dissipation and, together with the smoothness of operation, to compare three different embeddable mechanisms. Moreover, the integration of a linear encoder allowed measuring the instantaneous end-effector position on a non-actuated linear guideway, consequently knowing the motor torque value and the force applied by the robot to the user. This has been compared to the interaction force estimated from the motor torques without the linear sensor. The error assessed between the force measured with the encoder and estimated without it is about 12.9%. These results demonstrate the importance of this new embedded system to detect human–machine interaction forces in an accurate way and prevent safety issues. © The Author(s) 2024
abstract_unstemmed	Abstract Nowadays, robots hold crucial roles in an increasing number of different fields, highlighting an ongoing transition to ever-closer collaboration between humans and machines. In this context, this new technological era has brought out safety issues and, consequently, robots need to be monitored with an appropriate control architecture and human–machine interaction forces should be correctly estimated. For this purpose, friction, inertia, external perturbation, and the intrinsic dynamic of the robots should be monitored. This specific work starts from the need to monitor human–robot interaction forces to ensure safety for users. A successful case study concerning the integration of additional sensors on a wrist robot that directly interacts with humans is shown. Its limits have been the inability to directly measure forces applied by users and the impossibility to know accurately the end-effector position. Firstly, introducing a force/torque sensor, the detection of the forces applied by the user to the robot has been enabled. The user’s force data have been used to measure force dissipation and, together with the smoothness of operation, to compare three different embeddable mechanisms. Moreover, the integration of a linear encoder allowed measuring the instantaneous end-effector position on a non-actuated linear guideway, consequently knowing the motor torque value and the force applied by the robot to the user. This has been compared to the interaction force estimated from the motor torques without the linear sensor. The error assessed between the force measured with the encoder and estimated without it is about 12.9%. These results demonstrate the importance of this new embedded system to detect human–machine interaction forces in an accurate way and prevent safety issues. © The Author(s) 2024
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title_short	Understanding human–robot interaction forces: a new mechanical solution
url	https://dx.doi.org/10.1007/s12008-024-01735-z
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author2	Albanese, Giulia Aurora Zenzeri, Jacopo Torazza, Diego Berselli, Giovanni
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up_date	2024-09-12T04:49:36.981Z
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fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">SPR057291241</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240912064717.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">240912s2024 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s12008-024-01735-z</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR057291241</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s12008-024-01735-z-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">690</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Pippo, Irene</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Understanding human–robot interaction forces: a new mechanical solution</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2024</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© The Author(s) 2024</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Nowadays, robots hold crucial roles in an increasing number of different fields, highlighting an ongoing transition to ever-closer collaboration between humans and machines. In this context, this new technological era has brought out safety issues and, consequently, robots need to be monitored with an appropriate control architecture and human–machine interaction forces should be correctly estimated. For this purpose, friction, inertia, external perturbation, and the intrinsic dynamic of the robots should be monitored. This specific work starts from the need to monitor human–robot interaction forces to ensure safety for users. A successful case study concerning the integration of additional sensors on a wrist robot that directly interacts with humans is shown. Its limits have been the inability to directly measure forces applied by users and the impossibility to know accurately the end-effector position. Firstly, introducing a force/torque sensor, the detection of the forces applied by the user to the robot has been enabled. The user’s force data have been used to measure force dissipation and, together with the smoothness of operation, to compare three different embeddable mechanisms. Moreover, the integration of a linear encoder allowed measuring the instantaneous end-effector position on a non-actuated linear guideway, consequently knowing the motor torque value and the force applied by the robot to the user. This has been compared to the interaction force estimated from the motor torques without the linear sensor. The error assessed between the force measured with the encoder and estimated without it is about 12.9%. These results demonstrate the importance of this new embedded system to detect human–machine interaction forces in an accurate way and prevent safety issues.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Human–robot interaction</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">CAD design</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mechanical design</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Interaction forces</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Virtual prototyping</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Albanese, Giulia Aurora</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zenzeri, Jacopo</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Torazza, Diego</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Berselli, Giovanni</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">International journal on interactive design and manufacturing</subfield><subfield code="d">Springer Paris, 2007</subfield><subfield code="g">18(2024), 7 vom: 07. März, Seite 4765-4774</subfield><subfield code="w">(DE-627)546503195</subfield><subfield code="w">(DE-600)2390733-2</subfield><subfield code="x">1955-2505</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:18</subfield><subfield code="g">year:2024</subfield><subfield code="g">number:7</subfield><subfield code="g">day:07</subfield><subfield code="g">month:03</subfield><subfield code="g">pages:4765-4774</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://dx.doi.org/10.1007/s12008-024-01735-z</subfield><subfield code="m">X:SPRINGER</subfield><subfield code="x">Resolving-System</subfield><subfield code="z">kostenfrei</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_0</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_SPRINGER</subfield></datafield><datafield tag="912" ind1=" " 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