Pub Date : 2019-04-01DOI: 10.1109/ISMR.2019.8710196
Adolfo Perrusquía, Wen Yu
Usually human-robot interaction is in task space, while the robot control is in joint space. In order to transform the forces/torques from robot joints to the end effector, Jacobian is needed, which includes linear and angular velocities Jacobians. Since the joint positions are coupled, the Jacobian is very complex. In this paper, we only use orientations of the end-effector and the angular velocities Jacobian by considering human in the control loop. Since the angular velocities are decoupled, the human-robot interaction becomes very simple. We simplify normal admittance control by only using the torques of human. This simple method avoids the kinematics calculation. Real time experiments are presented with the 2-DOF pan and tilt robot and a 4-DOF robot.
{"title":"Task space human-robot interaction using angular velocity Jacobian","authors":"Adolfo Perrusquía, Wen Yu","doi":"10.1109/ISMR.2019.8710196","DOIUrl":"https://doi.org/10.1109/ISMR.2019.8710196","url":null,"abstract":"Usually human-robot interaction is in task space, while the robot control is in joint space. In order to transform the forces/torques from robot joints to the end effector, Jacobian is needed, which includes linear and angular velocities Jacobians. Since the joint positions are coupled, the Jacobian is very complex. In this paper, we only use orientations of the end-effector and the angular velocities Jacobian by considering human in the control loop. Since the angular velocities are decoupled, the human-robot interaction becomes very simple. We simplify normal admittance control by only using the torques of human. This simple method avoids the kinematics calculation. Real time experiments are presented with the 2-DOF pan and tilt robot and a 4-DOF robot.","PeriodicalId":404745,"journal":{"name":"2019 International Symposium on Medical Robotics (ISMR)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133562348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-04-01DOI: 10.1109/ISMR.2019.8710193
Kihan Park, Phillip Tran, N. Deaton, J. Desai
Flexible sensors using functional materials have been extensively studied due to their significant potential in biomedical applications such as wearable electronics. Multi-walled carbon nanotubes (MWCNTs) that have excellent electrical conductivity enables polydimethylsiloxane (PDMS), a biocompatible silicone, to become conductive and piezoresistive as a nano-filler material in the polymer. Dispersion methods of MWCNT in PDMS and characterization of MWCNT/PDMS elastomers are analyzed to establish an optimal fabrication process. The fabricated MWCNT/PDMS-based flexible sensors have been implemented for two medical applications: 1) tactile sensing for a robotic hand for rehabilitation tasks and 2) strain sensing within a needle for in situ tissue characterization. Since the developed piezoresistive type of sensors are highly flexible, responsive, easy to scale, cost-effective, simply packaged, and biocompatible, they have numerous applications in the biomedical field.
{"title":"Multi-walled Carbon Nanotube (MWCNT)/PDMS-based Flexible Sensor for Medical Applications","authors":"Kihan Park, Phillip Tran, N. Deaton, J. Desai","doi":"10.1109/ISMR.2019.8710193","DOIUrl":"https://doi.org/10.1109/ISMR.2019.8710193","url":null,"abstract":"Flexible sensors using functional materials have been extensively studied due to their significant potential in biomedical applications such as wearable electronics. Multi-walled carbon nanotubes (MWCNTs) that have excellent electrical conductivity enables polydimethylsiloxane (PDMS), a biocompatible silicone, to become conductive and piezoresistive as a nano-filler material in the polymer. Dispersion methods of MWCNT in PDMS and characterization of MWCNT/PDMS elastomers are analyzed to establish an optimal fabrication process. The fabricated MWCNT/PDMS-based flexible sensors have been implemented for two medical applications: 1) tactile sensing for a robotic hand for rehabilitation tasks and 2) strain sensing within a needle for in situ tissue characterization. Since the developed piezoresistive type of sensors are highly flexible, responsive, easy to scale, cost-effective, simply packaged, and biocompatible, they have numerous applications in the biomedical field.","PeriodicalId":404745,"journal":{"name":"2019 International Symposium on Medical Robotics (ISMR)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128010467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-28DOI: 10.1109/ISMR.2019.8710192
M. S. Yasar, David Evans, H. Alemzadeh
Robotic-assisted minimally invasive surgery (MIS) has enabled procedures with increased precision and dexterity, but surgical robots are still open loop and require surgeons to work with a tele-operation console providing only limited visual feedback. In this setting, mechanical failures, software faults, or human errors might lead to adverse events resulting in patient complications or fatalities. We argue that impending adverse events could be detected and mitigated by applying context-specific safety constraints on the motions of the robot. We present a context-aware safety monitoring system which segments a surgical task into subtasks using kinematics data and monitors safety constraints specific to each subtask. To test our hypothesis about context specificity of safety constraints, we analyze recorded demonstrations of dry-lab surgical tasks collected from the JIGSAWS database as well as from experiments we conducted on a Raven II surgical robot. Analysis of the trajectory data shows that each subtask of a given surgical procedure has consistent safety constraints across multiple demonstrations by different subjects. Our preliminary results show that violations of these safety constraints lead to unsafe events, and there is often sufficient time between the constraint violation and the safety-critical event to allow for a corrective action.
{"title":"Context-aware Monitoring in Robotic Surgery","authors":"M. S. Yasar, David Evans, H. Alemzadeh","doi":"10.1109/ISMR.2019.8710192","DOIUrl":"https://doi.org/10.1109/ISMR.2019.8710192","url":null,"abstract":"Robotic-assisted minimally invasive surgery (MIS) has enabled procedures with increased precision and dexterity, but surgical robots are still open loop and require surgeons to work with a tele-operation console providing only limited visual feedback. In this setting, mechanical failures, software faults, or human errors might lead to adverse events resulting in patient complications or fatalities. We argue that impending adverse events could be detected and mitigated by applying context-specific safety constraints on the motions of the robot. We present a context-aware safety monitoring system which segments a surgical task into subtasks using kinematics data and monitors safety constraints specific to each subtask. To test our hypothesis about context specificity of safety constraints, we analyze recorded demonstrations of dry-lab surgical tasks collected from the JIGSAWS database as well as from experiments we conducted on a Raven II surgical robot. Analysis of the trajectory data shows that each subtask of a given surgical procedure has consistent safety constraints across multiple demonstrations by different subjects. Our preliminary results show that violations of these safety constraints lead to unsafe events, and there is often sufficient time between the constraint violation and the safety-critical event to allow for a corrective action.","PeriodicalId":404745,"journal":{"name":"2019 International Symposium on Medical Robotics (ISMR)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117319974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-20DOI: 10.1109/ISMR.2019.8710179
S. Sefati, Rachel A. Hegeman, F. Alambeigi, I. Iordachita, M. Armand
Conventional shape sensing techniques using Fiber Bragg Grating (FBG) involve finding the curvature at discrete FBG active areas and integrating curvature over the length of the continuum dexterous manipulator (CDM) for tip position estimation (TPE). However, due to limited number of sensing locations and many geometrical assumptions, these methods are prone to large error propagation especially when the CDM undergoes large deflections. In this paper, we study the complications of using the conventional TPE methods that are dependent on sensor model and propose a new data-driven method that overcomes these challenges. The proposed method consists of a regression model that takes FBG wavelength raw data as input and directly estimates the CDM’s tip position. This model is pre-operatively (off-line) trained on position information from optical trackers/cameras (as the ground truth) and it intra-operatively (on-line) estimates CDM tip position using only the FBG wavelength data. The method’s performance is evaluated on a CDM developed for orthopedic applications, and the results are compared to conventional model-dependent methods during large deflection bendings. Mean absolute TPE error (and standard deviation) of 1.52 (0.67) mm and 0.11 (0.1) mm with maximum absolute errors of 3.63 mm and 0.62 mm for the conventional and the proposed data-driven techniques were obtained, respectively. These results demonstrate a significant out-performance of the proposed data-driven approach versus the conventional estimation technique.
{"title":"FBG-Based Position Estimation of Highly Deformable Continuum Manipulators: Model-Dependent vs. Data-Driven Approaches","authors":"S. Sefati, Rachel A. Hegeman, F. Alambeigi, I. Iordachita, M. Armand","doi":"10.1109/ISMR.2019.8710179","DOIUrl":"https://doi.org/10.1109/ISMR.2019.8710179","url":null,"abstract":"Conventional shape sensing techniques using Fiber Bragg Grating (FBG) involve finding the curvature at discrete FBG active areas and integrating curvature over the length of the continuum dexterous manipulator (CDM) for tip position estimation (TPE). However, due to limited number of sensing locations and many geometrical assumptions, these methods are prone to large error propagation especially when the CDM undergoes large deflections. In this paper, we study the complications of using the conventional TPE methods that are dependent on sensor model and propose a new data-driven method that overcomes these challenges. The proposed method consists of a regression model that takes FBG wavelength raw data as input and directly estimates the CDM’s tip position. This model is pre-operatively (off-line) trained on position information from optical trackers/cameras (as the ground truth) and it intra-operatively (on-line) estimates CDM tip position using only the FBG wavelength data. The method’s performance is evaluated on a CDM developed for orthopedic applications, and the results are compared to conventional model-dependent methods during large deflection bendings. Mean absolute TPE error (and standard deviation) of 1.52 (0.67) mm and 0.11 (0.1) mm with maximum absolute errors of 3.63 mm and 0.62 mm for the conventional and the proposed data-driven techniques were obtained, respectively. These results demonstrate a significant out-performance of the proposed data-driven approach versus the conventional estimation technique.","PeriodicalId":404745,"journal":{"name":"2019 International Symposium on Medical Robotics (ISMR)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127589015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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