Pub Date : 2016-06-26DOI: 10.1109/BIOROB.2016.7523733
J. Ochoa, D. Sternad, N. Hogan
Unlike upper-extremity robotic therapy, robotic therapy of lower extremities has not matched the effectiveness of human-administered approaches. We hypothesize that this may stem from inadvertent interference with natural movement control and investigated the oscillatory dynamics of human locomotion. Specifically, we assessed gait entrainment to periodic mechanical perturbations. Because the treadmills used in most studies necessarily interact with the dynamics of natural walking, we compared our experimental intervention during gait entrainment in treadmill and overground walking. Fourteen healthy subjects walked overground and on a treadmill while wearing an exoskeletal ankle robot which exerted short plantarflexion torque pulses at periods 50 ms shorter or longer than the subjects' preferred stride period. Entrainment to the periodic perturbation occurred in all conditions, however more readily in overground walking. In all cases, the stride period phase-locked with the torque pulse at `push-off' such that it assisted propulsion. This entrainment of the stride period and its sensitivity to context indicate the subtlety and adaptability of human walking. Our observations suggest new avenues for gait rehabilitation and implications for exoskeleton design and legged locomotion research.
{"title":"Entrainment of overground human walking to mechanical perturbations at the ankle joint","authors":"J. Ochoa, D. Sternad, N. Hogan","doi":"10.1109/BIOROB.2016.7523733","DOIUrl":"https://doi.org/10.1109/BIOROB.2016.7523733","url":null,"abstract":"Unlike upper-extremity robotic therapy, robotic therapy of lower extremities has not matched the effectiveness of human-administered approaches. We hypothesize that this may stem from inadvertent interference with natural movement control and investigated the oscillatory dynamics of human locomotion. Specifically, we assessed gait entrainment to periodic mechanical perturbations. Because the treadmills used in most studies necessarily interact with the dynamics of natural walking, we compared our experimental intervention during gait entrainment in treadmill and overground walking. Fourteen healthy subjects walked overground and on a treadmill while wearing an exoskeletal ankle robot which exerted short plantarflexion torque pulses at periods 50 ms shorter or longer than the subjects' preferred stride period. Entrainment to the periodic perturbation occurred in all conditions, however more readily in overground walking. In all cases, the stride period phase-locked with the torque pulse at `push-off' such that it assisted propulsion. This entrainment of the stride period and its sensitivity to context indicate the subtlety and adaptability of human walking. Our observations suggest new avenues for gait rehabilitation and implications for exoskeleton design and legged locomotion research.","PeriodicalId":235222,"journal":{"name":"2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125176409","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 : 2016-06-26DOI: 10.1109/BIOROB.2016.7523622
Yongping Pan, Tairen Sun, Haoyong Yu
This paper focuses on biomimetic hybrid feedback feedforward (HFF) learning for robot motion control. Existing HFF robot motion control approaches have a major problem that accurate estimation of the robotic dynamics, which is crucial for mimicking biological control, is not taken into account. In this study, a composite learning technique is presented to achieve fast and accurate estimation of the robotic dynamics in robot motion control without a stringent persistent-excitation (PE) condition. The control architecture includes a proportional-derivative (PD) controller acting as a feedback servo machine and an estimation model acting as a feedforward predictive machine. In the composite learning, a time-interval integral of a filtered regressor is utilized to construct a prediction error, and both the prediction error and a filtered tracking error are used to update parametric estimates. Semiglobal exponential stability of the closed-loop system is rigorously established under an interval-excitation (IE) condition which is much weaker than the PE condition. Simulation results have been provided to demonstrate effectiveness and superiority of the proposed approach.
{"title":"Biomimetic composite learning for robot motion control","authors":"Yongping Pan, Tairen Sun, Haoyong Yu","doi":"10.1109/BIOROB.2016.7523622","DOIUrl":"https://doi.org/10.1109/BIOROB.2016.7523622","url":null,"abstract":"This paper focuses on biomimetic hybrid feedback feedforward (HFF) learning for robot motion control. Existing HFF robot motion control approaches have a major problem that accurate estimation of the robotic dynamics, which is crucial for mimicking biological control, is not taken into account. In this study, a composite learning technique is presented to achieve fast and accurate estimation of the robotic dynamics in robot motion control without a stringent persistent-excitation (PE) condition. The control architecture includes a proportional-derivative (PD) controller acting as a feedback servo machine and an estimation model acting as a feedforward predictive machine. In the composite learning, a time-interval integral of a filtered regressor is utilized to construct a prediction error, and both the prediction error and a filtered tracking error are used to update parametric estimates. Semiglobal exponential stability of the closed-loop system is rigorously established under an interval-excitation (IE) condition which is much weaker than the PE condition. Simulation results have been provided to demonstrate effectiveness and superiority of the proposed approach.","PeriodicalId":235222,"journal":{"name":"2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131482949","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 : 2016-06-26DOI: 10.1109/BIOROB.2016.7523711
C. B. Moretti, Ricardo C. Joaquim, Thais T. Terranova, L. Battistella, S. Mazzoleni, G. Caurin
Aiming to perform an extraction of features which are strongly related to hemiparesis, this work describes a case study involving the efforts of patients in upper-limb rehabilitation, diagnosed with such pathology. Expressed as data (kinematic and dynamic measures), patients' performance were sensed and stored by a single InMotion Arm robotic device for further analysis. It was applied a Knowledge Discovery roadmap over collected data in order to preprocess, transform and perform data mining through machine learning methods. Our efforts culminated in a pattern classification with the abilty to distinguish hemiparetic sides with an accuracy rate of 94%, having 8 features of rehabilitation performance feeding the input. Interpreting the obtained feature structure, it was observed that force-related attributes are more significant to the composition of the extracted pattern.
{"title":"Knowledge Discovery strategy over patient performance data towards the extraction of hemiparesis-inherent features: A case study","authors":"C. B. Moretti, Ricardo C. Joaquim, Thais T. Terranova, L. Battistella, S. Mazzoleni, G. Caurin","doi":"10.1109/BIOROB.2016.7523711","DOIUrl":"https://doi.org/10.1109/BIOROB.2016.7523711","url":null,"abstract":"Aiming to perform an extraction of features which are strongly related to hemiparesis, this work describes a case study involving the efforts of patients in upper-limb rehabilitation, diagnosed with such pathology. Expressed as data (kinematic and dynamic measures), patients' performance were sensed and stored by a single InMotion Arm robotic device for further analysis. It was applied a Knowledge Discovery roadmap over collected data in order to preprocess, transform and perform data mining through machine learning methods. Our efforts culminated in a pattern classification with the abilty to distinguish hemiparetic sides with an accuracy rate of 94%, having 8 features of rehabilitation performance feeding the input. Interpreting the obtained feature structure, it was observed that force-related attributes are more significant to the composition of the extracted pattern.","PeriodicalId":235222,"journal":{"name":"2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128272407","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 : 2016-06-26DOI: 10.1109/BIOROB.2016.7523614
Shunsuke Nansai, M. R. Elara, M. Iwase
A real snake has simple figure like a string, and has highly adaptability corresponding to the environments/tasks. A snake-like robot mimics such highly adaptability of the real snake, is expected as an adaptable robot corresponding to the environments/tasks. Many literatures have reported with respect to locomotion controls of the snake-like robot, but haven't reported studies for applications. However, enhancement of the applications is required in real scenes of which the snake-like robot is expected to work. This paper reports to design the force controller to realize the cutting task by the snake-like robot, as a leading example of the force control in the real scenes. Since the force control in the feed direction and the servo control in its normal direction are required in order to realize the cutting task, the Dynamic Hybrid Position/Force Control System is designed. The Virtual Internal Model based on the impedance model is utilized as the force control method. The Model Following Servo Control System utilizing the Virtual Internal Model based on the impedance model is designed, and the Dynamic Hybrid Position/Force Control System is realized. Effectiveness of the designed control system is verified through a numerical simulation.
{"title":"Dynamic Hybrid Position Force Control using Virtual Internal Model to realize a cutting task by a snake-like robot","authors":"Shunsuke Nansai, M. R. Elara, M. Iwase","doi":"10.1109/BIOROB.2016.7523614","DOIUrl":"https://doi.org/10.1109/BIOROB.2016.7523614","url":null,"abstract":"A real snake has simple figure like a string, and has highly adaptability corresponding to the environments/tasks. A snake-like robot mimics such highly adaptability of the real snake, is expected as an adaptable robot corresponding to the environments/tasks. Many literatures have reported with respect to locomotion controls of the snake-like robot, but haven't reported studies for applications. However, enhancement of the applications is required in real scenes of which the snake-like robot is expected to work. This paper reports to design the force controller to realize the cutting task by the snake-like robot, as a leading example of the force control in the real scenes. Since the force control in the feed direction and the servo control in its normal direction are required in order to realize the cutting task, the Dynamic Hybrid Position/Force Control System is designed. The Virtual Internal Model based on the impedance model is utilized as the force control method. The Model Following Servo Control System utilizing the Virtual Internal Model based on the impedance model is designed, and the Dynamic Hybrid Position/Force Control System is realized. Effectiveness of the designed control system is verified through a numerical simulation.","PeriodicalId":235222,"journal":{"name":"2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130469287","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 : 2016-06-26DOI: 10.1109/BIOROB.2016.7523758
Rainier F. Natividad, C. Yeow
Cerebral Palsy (CP) is a perpetual disease that a patient endures throughout their entire lifetime. Motor impairment, that is a common symptom, must be permanently managed by the patient; however, evidence suggests that repetitive task practice (RTP) can help patients improve their motor skills. An initial version of a wearable, soft robotic, shoulder exosuit has been developed that may be used for RTP. The device is centered around an inflatable, fabric beam that facilitates abduction of the shoulder joint. The use of an inflatable beam has allowed the device to be extremely lightweight while still being able to deliver a considerable amount of bending moment. The actuator is initially in its deflated state; inflation of the actuator straightens it, applying a bending moment to the brachium that abducts the limb. Two overlapping sheets of fabric were hermetically sealed by applying localized heat at the edges. Actuators were then anchored to the shoulder and inserted to a sleeve attached to the brachium. Position control was achieved by applying varying magnitudes of pressure. Preliminary testing exhibited successful abduction on a mannequin and a healthy subject.
{"title":"Development of a soft robotic shoulder assistive device for shoulder abduction","authors":"Rainier F. Natividad, C. Yeow","doi":"10.1109/BIOROB.2016.7523758","DOIUrl":"https://doi.org/10.1109/BIOROB.2016.7523758","url":null,"abstract":"Cerebral Palsy (CP) is a perpetual disease that a patient endures throughout their entire lifetime. Motor impairment, that is a common symptom, must be permanently managed by the patient; however, evidence suggests that repetitive task practice (RTP) can help patients improve their motor skills. An initial version of a wearable, soft robotic, shoulder exosuit has been developed that may be used for RTP. The device is centered around an inflatable, fabric beam that facilitates abduction of the shoulder joint. The use of an inflatable beam has allowed the device to be extremely lightweight while still being able to deliver a considerable amount of bending moment. The actuator is initially in its deflated state; inflation of the actuator straightens it, applying a bending moment to the brachium that abducts the limb. Two overlapping sheets of fabric were hermetically sealed by applying localized heat at the edges. Actuators were then anchored to the shoulder and inserted to a sleeve attached to the brachium. Position control was achieved by applying varying magnitudes of pressure. Preliminary testing exhibited successful abduction on a mannequin and a healthy subject.","PeriodicalId":235222,"journal":{"name":"2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123341696","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 : 2016-06-26DOI: 10.1109/BIOROB.2016.7523738
Simon Rudt, Marco Moos, Solange Seppey, R. Riener, L. Marchal-Crespo
Robot-aided gait training has been presented as a promising technique to improve rehabilitation in patients with neurological lesions. Although robotic guidance is often used to reduce performance errors while practicing, there is currently little evidence that robotic guidance is more beneficial for human motor learning than unassisted practice. Research on motor learning has emphasized that movement errors drive motor adaptation. Thereby, robotic algorithms that augment errors rather than decrease them have a great potential to provoke better motor learning. In this paper, we present a novel control algorithm that modulates movement errors by limiting dangerous and discouraging large errors with haptic guidance, while augmenting awareness of task relevant errors by means of error amplification. We also designed a controller that applies random disturbance torques that can work on top of the error-modulating controller. The controllers were evaluated using robotic testing. The error-modulating controller resulted in larger errors due to error amplification, but limited the maximum deviation from the desired pattern, thanks to haptic guidance. Adding random disturbance torques increased gait variability. The combination of the random disturbance and error-modulating controllers increased the kinematic errors and gait variability, while limited large errors, providing an excellent framework to enhance motor learning.
{"title":"Towards more efficient robotic gait training: A novel controller to modulate movement errors","authors":"Simon Rudt, Marco Moos, Solange Seppey, R. Riener, L. Marchal-Crespo","doi":"10.1109/BIOROB.2016.7523738","DOIUrl":"https://doi.org/10.1109/BIOROB.2016.7523738","url":null,"abstract":"Robot-aided gait training has been presented as a promising technique to improve rehabilitation in patients with neurological lesions. Although robotic guidance is often used to reduce performance errors while practicing, there is currently little evidence that robotic guidance is more beneficial for human motor learning than unassisted practice. Research on motor learning has emphasized that movement errors drive motor adaptation. Thereby, robotic algorithms that augment errors rather than decrease them have a great potential to provoke better motor learning. In this paper, we present a novel control algorithm that modulates movement errors by limiting dangerous and discouraging large errors with haptic guidance, while augmenting awareness of task relevant errors by means of error amplification. We also designed a controller that applies random disturbance torques that can work on top of the error-modulating controller. The controllers were evaluated using robotic testing. The error-modulating controller resulted in larger errors due to error amplification, but limited the maximum deviation from the desired pattern, thanks to haptic guidance. Adding random disturbance torques increased gait variability. The combination of the random disturbance and error-modulating controllers increased the kinematic errors and gait variability, while limited large errors, providing an excellent framework to enhance motor learning.","PeriodicalId":235222,"journal":{"name":"2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129482911","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 : 2016-06-26DOI: 10.1109/BIOROB.2016.7523627
Kathia Chenane, Y. Touati, L. Boubchir, B. Daachi, A. A. Chérif
One of the objectives of the control using the human thought is to make useful robotic systems for persons with high dependency (quadriplegics, paraplegics, etc.). When the human subject is not able to move his limbs, upper or lower, he is no longer able to perform basic and necessary tasks in his daily life. Recently, robotic systems have reached a very advanced level. For example, humanoid robots have become able to walk, recognize and carry objects simultaneously. On the other hand, wearable robots or exoskeletons can help dependent human subject to move and perform tasks previously difficult to imagine. Of course, all these robotic systems cannot perform these tasks except if they are fitted with advanced control schemes. To make these robotic systems, having already some intelligence, more useful, many researchers have studied the problem of controllers based on the user thought. The real challenge is to translate/classify correctly the thought of the user into robotic actions. When the brain activities are not correctly classified or the action thought by the user is not quite performed, it is important to discover it at time. This allows us to update the classifier/controller parameters in order to interpret more precisely the brain activities concerning the following action. This paper deals with looking for relevant prior knowledge that can anticipate any classification error. Thereafter, we propose some reflections regarding the control of robots by passive thought. Our analysis and results are based on the brain machine interface (BMI) using the Steady State Visual Evoked Potentials technique (SSVEP).
{"title":"Algorithms of control by thought in robotics: Active and passive BMIs based on prior knowledge","authors":"Kathia Chenane, Y. Touati, L. Boubchir, B. Daachi, A. A. Chérif","doi":"10.1109/BIOROB.2016.7523627","DOIUrl":"https://doi.org/10.1109/BIOROB.2016.7523627","url":null,"abstract":"One of the objectives of the control using the human thought is to make useful robotic systems for persons with high dependency (quadriplegics, paraplegics, etc.). When the human subject is not able to move his limbs, upper or lower, he is no longer able to perform basic and necessary tasks in his daily life. Recently, robotic systems have reached a very advanced level. For example, humanoid robots have become able to walk, recognize and carry objects simultaneously. On the other hand, wearable robots or exoskeletons can help dependent human subject to move and perform tasks previously difficult to imagine. Of course, all these robotic systems cannot perform these tasks except if they are fitted with advanced control schemes. To make these robotic systems, having already some intelligence, more useful, many researchers have studied the problem of controllers based on the user thought. The real challenge is to translate/classify correctly the thought of the user into robotic actions. When the brain activities are not correctly classified or the action thought by the user is not quite performed, it is important to discover it at time. This allows us to update the classifier/controller parameters in order to interpret more precisely the brain activities concerning the following action. This paper deals with looking for relevant prior knowledge that can anticipate any classification error. Thereafter, we propose some reflections regarding the control of robots by passive thought. Our analysis and results are based on the brain machine interface (BMI) using the Steady State Visual Evoked Potentials technique (SSVEP).","PeriodicalId":235222,"journal":{"name":"2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114629792","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 : 2016-06-26DOI: 10.1109/BIOROB.2016.7523759
S. Pedro, Paulo Menezes
This paper proposes a solution that can be used to develop an assistive device to help people that have tracheostomies to make use of verbal communication. Based on the analysis of video images, we propose to develop a system suitable to be used to produce vowel sounds. Exploring the McGurk effect, we expect seeing the mouth movements and listening to the corresponding vowels to be sufficient for improving the understanding of “speechless people”. We conducted three experiments which results show that: 1) just adding vowels' sounds can improve the understandability of the lip reading process; 2) it is possible to detect and to classify vowel-related mouth movements; 3) people can adapt mouth movements to make the system generate the intended vowel, even when it was initially adapted to another person.
{"title":"Exploiting the importance of vowelized sounds in speech comprehension: An application for assisting speechless people","authors":"S. Pedro, Paulo Menezes","doi":"10.1109/BIOROB.2016.7523759","DOIUrl":"https://doi.org/10.1109/BIOROB.2016.7523759","url":null,"abstract":"This paper proposes a solution that can be used to develop an assistive device to help people that have tracheostomies to make use of verbal communication. Based on the analysis of video images, we propose to develop a system suitable to be used to produce vowel sounds. Exploring the McGurk effect, we expect seeing the mouth movements and listening to the corresponding vowels to be sufficient for improving the understanding of “speechless people”. We conducted three experiments which results show that: 1) just adding vowels' sounds can improve the understandability of the lip reading process; 2) it is possible to detect and to classify vowel-related mouth movements; 3) people can adapt mouth movements to make the system generate the intended vowel, even when it was initially adapted to another person.","PeriodicalId":235222,"journal":{"name":"2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130297756","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 : 2016-06-26DOI: 10.1109/BIOROB.2016.7523715
Christina Ramer, T. Lichtenegger, J. Sessner, M. Landgraf, J. Franke
Based on a previously published version of a first prototypic jogging navigation system for visually impaired and blind people, this paper presents an adaptive lane detection method that extents the use on standard running tracks to general and less structured paths. Additional and supporting developments refer to an active camera stabilization, the improved intuitive vibration feedback and the integrated and embedded mechatronic system setup.
{"title":"An adaptive, color based lane detection of a wearable jogging navigation system for visually impaired on less structured paths","authors":"Christina Ramer, T. Lichtenegger, J. Sessner, M. Landgraf, J. Franke","doi":"10.1109/BIOROB.2016.7523715","DOIUrl":"https://doi.org/10.1109/BIOROB.2016.7523715","url":null,"abstract":"Based on a previously published version of a first prototypic jogging navigation system for visually impaired and blind people, this paper presents an adaptive lane detection method that extents the use on standard running tracks to general and less structured paths. Additional and supporting developments refer to an active camera stabilization, the improved intuitive vibration feedback and the integrated and embedded mechatronic system setup.","PeriodicalId":235222,"journal":{"name":"2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131159143","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 : 2016-06-26DOI: 10.1109/BIOROB.2016.7523598
Antonia Tzemanaki, L. Fracczak, D. Gillatt, A. Koupparis, C. Melhuish, R. Persad, E. Rowe, A. Pipe, S. Dogramadzi
While multi-fingered robotic hands have been developed for decades, none has been used for surgical operations. μAngelo is an anthropomorphic master-slave system for teleoperated robot-assisted surgery. As part of this system, this paper focuses on its slave instrument, a miniature three-digit hand. The design of the mechanism of such a manipulator poses a challenge due to the required miniaturization and the many active degrees of freedom. As the instrument has a human-centered design, its relation to the human hand is discussed. Two ways of routing its cable-driven mechanism are investigated and the method of deriving the input-output functions that drive the mechanism is presented.
{"title":"Design of a multi-DOF cable-driven mechanism of a miniature serial manipulator for robot-assisted minimally invasive surgery","authors":"Antonia Tzemanaki, L. Fracczak, D. Gillatt, A. Koupparis, C. Melhuish, R. Persad, E. Rowe, A. Pipe, S. Dogramadzi","doi":"10.1109/BIOROB.2016.7523598","DOIUrl":"https://doi.org/10.1109/BIOROB.2016.7523598","url":null,"abstract":"While multi-fingered robotic hands have been developed for decades, none has been used for surgical operations. μAngelo is an anthropomorphic master-slave system for teleoperated robot-assisted surgery. As part of this system, this paper focuses on its slave instrument, a miniature three-digit hand. The design of the mechanism of such a manipulator poses a challenge due to the required miniaturization and the many active degrees of freedom. As the instrument has a human-centered design, its relation to the human hand is discussed. Two ways of routing its cable-driven mechanism are investigated and the method of deriving the input-output functions that drive the mechanism is presented.","PeriodicalId":235222,"journal":{"name":"2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131182363","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：