Pub Date : 2015-07-27DOI: 10.1109/ICAR.2015.7251521
Joelle Al Hage, Nourdine Ait Tmazirte, Maan El Badaoui El Najjar, D. Pomorski
Integrity monitoring for a positioning method permit us to guarantee a high integrity localization which is needed for an autonomous navigation system. Different approaches for localization integrity monitoring have been developed. In this paper, we propose a Fault Detection and Exclusion (FDE) method based on information metrics since it provides tools that allow designing residual test that increase the integrity of localization. A residual test based on the Kullback-Leibler divergence (KLD) is elaborated. It is integrated in a FDE architecture applied to localization using a tightly coupled multi-sensor (GPS and odometer) data fusion method.
{"title":"Fault detection and exclusion method for a tightly coupled localization system","authors":"Joelle Al Hage, Nourdine Ait Tmazirte, Maan El Badaoui El Najjar, D. Pomorski","doi":"10.1109/ICAR.2015.7251521","DOIUrl":"https://doi.org/10.1109/ICAR.2015.7251521","url":null,"abstract":"Integrity monitoring for a positioning method permit us to guarantee a high integrity localization which is needed for an autonomous navigation system. Different approaches for localization integrity monitoring have been developed. In this paper, we propose a Fault Detection and Exclusion (FDE) method based on information metrics since it provides tools that allow designing residual test that increase the integrity of localization. A residual test based on the Kullback-Leibler divergence (KLD) is elaborated. It is integrated in a FDE architecture applied to localization using a tightly coupled multi-sensor (GPS and odometer) data fusion method.","PeriodicalId":432004,"journal":{"name":"2015 International Conference on Advanced Robotics (ICAR)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122606134","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 : 2015-07-27DOI: 10.1109/ICAR.2015.7251517
Nuri Ozalp, U. Ayan, Erhan Öztop
This research is focused on the cooperative multi-task assignment problem for heterogeneous UAVs, where a set of multiple tasks, each requiring a predetermined number of UAVs, have to be completed at specific locations. We modeled this as an optimization problem to minimize the number of uncompleted tasks while also minimizing total airtime and total distance traveled by all the UAVs. By taking into account the UAV flight capacities. For the solution of the problem, we adopted a multi-Traveling Salesman Problem (mTSP) method [1] and designed a new genetic structure for it so that it can be applied to cooperative multi-task assignment problems. Furthermore, we developed two domain specific mutation operators to improve the quality of the solutions in terms of number of uncompleted tasks, total airtime and total distance traveled by all the UAVs. The simulation experiments showed that these operators significantly improve the solution quality. Our main contributions are the application of the Multi Structure Genetic Algorithm (MSGA) to cooperative multi-task assignment problem and the development of two novel mutation operators to improve the solution of MSGA.
{"title":"Cooperative multi-task assignment for heterogonous UAVs","authors":"Nuri Ozalp, U. Ayan, Erhan Öztop","doi":"10.1109/ICAR.2015.7251517","DOIUrl":"https://doi.org/10.1109/ICAR.2015.7251517","url":null,"abstract":"This research is focused on the cooperative multi-task assignment problem for heterogeneous UAVs, where a set of multiple tasks, each requiring a predetermined number of UAVs, have to be completed at specific locations. We modeled this as an optimization problem to minimize the number of uncompleted tasks while also minimizing total airtime and total distance traveled by all the UAVs. By taking into account the UAV flight capacities. For the solution of the problem, we adopted a multi-Traveling Salesman Problem (mTSP) method [1] and designed a new genetic structure for it so that it can be applied to cooperative multi-task assignment problems. Furthermore, we developed two domain specific mutation operators to improve the quality of the solutions in terms of number of uncompleted tasks, total airtime and total distance traveled by all the UAVs. The simulation experiments showed that these operators significantly improve the solution quality. Our main contributions are the application of the Multi Structure Genetic Algorithm (MSGA) to cooperative multi-task assignment problem and the development of two novel mutation operators to improve the solution of MSGA.","PeriodicalId":432004,"journal":{"name":"2015 International Conference on Advanced Robotics (ICAR)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115976118","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 : 2015-07-27DOI: 10.1109/ICAR.2015.7251479
Deniz Kerimoglu, Ö. Morgül, U. Saranlı
Passive dynamic walkers exhibit stable human-like walking on inclined planes. The simplest model of this behavior is the well known passive compass gait (PCG) model, which consists of a point mass at the hip and two stick legs. Due to their passive nature, these systems rely on a sloped ground to recover energy lost to ground collisions. A variety of methods have been proposed to eliminate this requirement by using different actuation methods. In this study, we propose a simple model to investigate how series elastic actuation at the ankle can be used to achieve stable walking on level ground. The structure we propose is designed to behave in a similar fashion to how humans utilize toe push-off prior to leg liftoff, and is intended to be used for controlling the ankle joint in a lower-body robotic orthosis. We present the derivation of the hybrid equations of motion for this model, resulting in a numerically computed return map for a single stride. We then numerically identify fixed points of this system and investigate their stability. We show that asymptotically stable walking on flat ground is possible with this model and identify the dependence of limit cycles and their stability on system parameters.
{"title":"Stability of a compass gait walking model with series elastic ankle actuation","authors":"Deniz Kerimoglu, Ö. Morgül, U. Saranlı","doi":"10.1109/ICAR.2015.7251479","DOIUrl":"https://doi.org/10.1109/ICAR.2015.7251479","url":null,"abstract":"Passive dynamic walkers exhibit stable human-like walking on inclined planes. The simplest model of this behavior is the well known passive compass gait (PCG) model, which consists of a point mass at the hip and two stick legs. Due to their passive nature, these systems rely on a sloped ground to recover energy lost to ground collisions. A variety of methods have been proposed to eliminate this requirement by using different actuation methods. In this study, we propose a simple model to investigate how series elastic actuation at the ankle can be used to achieve stable walking on level ground. The structure we propose is designed to behave in a similar fashion to how humans utilize toe push-off prior to leg liftoff, and is intended to be used for controlling the ankle joint in a lower-body robotic orthosis. We present the derivation of the hybrid equations of motion for this model, resulting in a numerically computed return map for a single stride. We then numerically identify fixed points of this system and investigate their stability. We show that asymptotically stable walking on flat ground is possible with this model and identify the dependence of limit cycles and their stability on system parameters.","PeriodicalId":432004,"journal":{"name":"2015 International Conference on Advanced Robotics (ICAR)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116026436","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 : 2015-07-27DOI: 10.1109/ICAR.2015.7251524
A. Pandey, R. Gelin
Affordance, being one of the key building blocks behind how we interact with the environment, is also studied widely in robotics from different perspectives, for navigation, for task planning, etc. Therefore, the study is mostly focused on affordances of individual objects and for robot environment interaction, and such affordances have been mostly perceived through vision and physical interaction. However, in a human centered environment, for a robot to be socially intelligent and exhibit more natural interaction behavior, it should be able to learn affordances also through day-to-day verbal interaction and that too from the perspective of what does the presence of a specific set of objects affords to provide. In this paper, we will present the novel idea of verbal interaction based multi-object affordance learning and a framework to achieve that. Further, an instantiation of the framework on the real robot within office context is analyzed. Some of the potential future works and applications, such as fusing with activity pattern and interaction grounding will be briefly discussed.
{"title":"Human robot interaction can boost robot's affordance learning: A proof of concept","authors":"A. Pandey, R. Gelin","doi":"10.1109/ICAR.2015.7251524","DOIUrl":"https://doi.org/10.1109/ICAR.2015.7251524","url":null,"abstract":"Affordance, being one of the key building blocks behind how we interact with the environment, is also studied widely in robotics from different perspectives, for navigation, for task planning, etc. Therefore, the study is mostly focused on affordances of individual objects and for robot environment interaction, and such affordances have been mostly perceived through vision and physical interaction. However, in a human centered environment, for a robot to be socially intelligent and exhibit more natural interaction behavior, it should be able to learn affordances also through day-to-day verbal interaction and that too from the perspective of what does the presence of a specific set of objects affords to provide. In this paper, we will present the novel idea of verbal interaction based multi-object affordance learning and a framework to achieve that. Further, an instantiation of the framework on the real robot within office context is analyzed. Some of the potential future works and applications, such as fusing with activity pattern and interaction grounding will be briefly discussed.","PeriodicalId":432004,"journal":{"name":"2015 International Conference on Advanced Robotics (ICAR)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126696972","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 : 2015-07-27DOI: 10.1109/ICAR.2015.7251473
M. Tagliabue, N. Francis, Yaoyao Hao, Margaux Duret, T. Brochier, A. Riehle, M. Maier, S. Eskiizmirliler
This study focuses on the estimation of kinematic and kinetic information during two-digit grasping using frequency decoding of motor cortex spike trains for brain machine interface applications. Neural data were recorded by a 100-microelectrode array implanted in the motor cortex of one monkey performing instructed reach-grasp-and-pull movements. Decoding of neural data was performed by two different algorithms: i) through Artificial Neural Networks (ANN) consisting of a multi layer perceptron (MLP), and ii) by a Support Vector Machine (SVM) with linear kernel function. Decoding aimed at classifying the upcoming grip type (precision grip vs. side grip) as well as the required grip force (low vs. high). We then used the decoded information to reproduce the monkey's movement on a robotic platform consisting of a two-finger, eleven degrees of freedom (DoF) robotic hand carried by a six DoF robotic arm. The results show that 1) in terms of performance there was no significant difference between ANN and SVM prediction. Both algorithms can be used for frequency decoding of multiple motor cortex spike trains: good performance was found for grip type prediction, less so for grip force. 2) For both algorithms the prediction error was significantly dependent on the position of the input time window associated to different stages of the instructed grasp movement. 3) The lower performance of grasp force prediction was improved by optimizing the neuronal population size presented to the ANN input layer on the basis of information redundancy.
{"title":"Estimation of two-digit grip type and grip force level by frequency decoding of motor cortex activity for a BMI application","authors":"M. Tagliabue, N. Francis, Yaoyao Hao, Margaux Duret, T. Brochier, A. Riehle, M. Maier, S. Eskiizmirliler","doi":"10.1109/ICAR.2015.7251473","DOIUrl":"https://doi.org/10.1109/ICAR.2015.7251473","url":null,"abstract":"This study focuses on the estimation of kinematic and kinetic information during two-digit grasping using frequency decoding of motor cortex spike trains for brain machine interface applications. Neural data were recorded by a 100-microelectrode array implanted in the motor cortex of one monkey performing instructed reach-grasp-and-pull movements. Decoding of neural data was performed by two different algorithms: i) through Artificial Neural Networks (ANN) consisting of a multi layer perceptron (MLP), and ii) by a Support Vector Machine (SVM) with linear kernel function. Decoding aimed at classifying the upcoming grip type (precision grip vs. side grip) as well as the required grip force (low vs. high). We then used the decoded information to reproduce the monkey's movement on a robotic platform consisting of a two-finger, eleven degrees of freedom (DoF) robotic hand carried by a six DoF robotic arm. The results show that 1) in terms of performance there was no significant difference between ANN and SVM prediction. Both algorithms can be used for frequency decoding of multiple motor cortex spike trains: good performance was found for grip type prediction, less so for grip force. 2) For both algorithms the prediction error was significantly dependent on the position of the input time window associated to different stages of the instructed grasp movement. 3) The lower performance of grasp force prediction was improved by optimizing the neuronal population size presented to the ANN input layer on the basis of information redundancy.","PeriodicalId":432004,"journal":{"name":"2015 International Conference on Advanced Robotics (ICAR)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126075968","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 : 2015-07-27DOI: 10.1109/ICAR.2015.7251431
Awais Ahmad, M. C. Cavusoglu, O. Bebek
Freehand Ultrasound technique is widely used in intraoperative biopsy procedures for detecting the volumes of interest. Freehand ultrasound probe is faster and flexible with 6 degrees of freedom. Thats why the imaging system must be calibrated in 3D space before integrating it with Robotics Biopsy System. In this paper we present a 3D space calibration method using a multipoint cross-wire phantom. The Ultrasound probe is attached to a robotic manipulator arm which moves it over the phantom in precise steps of distances and angles. The position and orientation of the probe is tracked by an optical tracking system. Optical markers are placed on the probe, phantom tank and the validation needle. The optical tracking system returns the position and orientation of the reference frames attached to these optical markers. The location of threads with reference to the frame of Ultrasound probe is found using this information. These values and the values returned by a mathematical model of the calibration box are used to construct the calibration matrix. The whole system is automated so it can process high number of frames which makes it rapid and more accurate. This process is used to calibrate the space for an automated needle insertion biopsy robot. The accuracy of the system was checked by a validation needle in 3D space. RMS error of the experiment groups on average was 1.67mm.
{"title":"Calibration of 2D Ultrasound in 3D space for Robotic biopsies","authors":"Awais Ahmad, M. C. Cavusoglu, O. Bebek","doi":"10.1109/ICAR.2015.7251431","DOIUrl":"https://doi.org/10.1109/ICAR.2015.7251431","url":null,"abstract":"Freehand Ultrasound technique is widely used in intraoperative biopsy procedures for detecting the volumes of interest. Freehand ultrasound probe is faster and flexible with 6 degrees of freedom. Thats why the imaging system must be calibrated in 3D space before integrating it with Robotics Biopsy System. In this paper we present a 3D space calibration method using a multipoint cross-wire phantom. The Ultrasound probe is attached to a robotic manipulator arm which moves it over the phantom in precise steps of distances and angles. The position and orientation of the probe is tracked by an optical tracking system. Optical markers are placed on the probe, phantom tank and the validation needle. The optical tracking system returns the position and orientation of the reference frames attached to these optical markers. The location of threads with reference to the frame of Ultrasound probe is found using this information. These values and the values returned by a mathematical model of the calibration box are used to construct the calibration matrix. The whole system is automated so it can process high number of frames which makes it rapid and more accurate. This process is used to calibrate the space for an automated needle insertion biopsy robot. The accuracy of the system was checked by a validation needle in 3D space. RMS error of the experiment groups on average was 1.67mm.","PeriodicalId":432004,"journal":{"name":"2015 International Conference on Advanced Robotics (ICAR)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127662856","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 : 2015-07-27DOI: 10.1109/ICAR.2015.7251457
V. Ivan, S. Vijayakumar
We propose a novel method for representing the interaction of a robot and an object. We create a virtual surface by taking a chain of linear segments attached to the robot links, we spatially extrude them in time, and we then compute the coverage of this surface around the object. Our approach uses a technique based on computation of electric flux, borrowed from electro dynamics. The advantage of using this method is that it is invariant to the relative transformations of the virtual surface, which makes it suitable as a complementary term in a cost function when constructing a multi-objective problem. We demonstrate the different types of interactions this method can represent, and how it can be integrated into trajectory optimisation based motion planners. We also demonstrate a practical application of such representation on a real robot.
{"title":"Space-time area coverage control for robot motion synthesis","authors":"V. Ivan, S. Vijayakumar","doi":"10.1109/ICAR.2015.7251457","DOIUrl":"https://doi.org/10.1109/ICAR.2015.7251457","url":null,"abstract":"We propose a novel method for representing the interaction of a robot and an object. We create a virtual surface by taking a chain of linear segments attached to the robot links, we spatially extrude them in time, and we then compute the coverage of this surface around the object. Our approach uses a technique based on computation of electric flux, borrowed from electro dynamics. The advantage of using this method is that it is invariant to the relative transformations of the virtual surface, which makes it suitable as a complementary term in a cost function when constructing a multi-objective problem. We demonstrate the different types of interactions this method can represent, and how it can be integrated into trajectory optimisation based motion planners. We also demonstrate a practical application of such representation on a real robot.","PeriodicalId":432004,"journal":{"name":"2015 International Conference on Advanced Robotics (ICAR)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132246844","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 : 2015-07-27DOI: 10.1109/ICAR.2015.7251512
Miha Deniša, A. Gams, A. Ude, T. Petrič
This paper addresses the problem of achieving high robot compliance while maintaining low tracking error without the use of dynamical models. The proposed approach uses programing by demonstration to learn new task related compliant movement. The presented Compliant Movement Primitives are a combination of 1) position trajectories, gained through human demonstration and encoded as Dynamical Movement Primitives and 2) corresponding torque trajectories encoded as a linear combination of radial basis functions. A set of example Compliant Movement Primitives is used with statistical generalization in order to execute previously unexplored tasks inside the training space. The proposed control approach and generalization was evaluated with a discrete pick-and-place task on a Kuka LWR robot. The evaluation showed a major decrease in tracking error compared to a classic feedback approach and no significant rise in tracking error while using generalized Compliant Movement Primitives.
{"title":"Generalization of discrete Compliant Movement Primitives","authors":"Miha Deniša, A. Gams, A. Ude, T. Petrič","doi":"10.1109/ICAR.2015.7251512","DOIUrl":"https://doi.org/10.1109/ICAR.2015.7251512","url":null,"abstract":"This paper addresses the problem of achieving high robot compliance while maintaining low tracking error without the use of dynamical models. The proposed approach uses programing by demonstration to learn new task related compliant movement. The presented Compliant Movement Primitives are a combination of 1) position trajectories, gained through human demonstration and encoded as Dynamical Movement Primitives and 2) corresponding torque trajectories encoded as a linear combination of radial basis functions. A set of example Compliant Movement Primitives is used with statistical generalization in order to execute previously unexplored tasks inside the training space. The proposed control approach and generalization was evaluated with a discrete pick-and-place task on a Kuka LWR robot. The evaluation showed a major decrease in tracking error compared to a classic feedback approach and no significant rise in tracking error while using generalized Compliant Movement Primitives.","PeriodicalId":432004,"journal":{"name":"2015 International Conference on Advanced Robotics (ICAR)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127851590","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 : 2015-07-27DOI: 10.1109/ICAR.2015.7251493
Ekin Basalp, K. Hara, H. Yamaura, D. Matsuura, Y. Takeda
In a previous study, a gait assistive device embodying actuators, known as Walking Assist Machine Using Crutches (WAMC), was proposed for people who suffer from lower limb disabilities. Experiments with healthy subjects show that WAMC can provide upright stance position and assisted forward gait to the user. However, the simplistic kinetostatic model used in gait analysis does not permit to obtain forces and torques acting on the system (user and WAMC) in detail. In this paper, an anthropometric 2D model which can investigate the gait characteristics of the system is proposed. Force and torques acting on the system parts can be guessed prior to the experiments if the user's height and weight are specified. This will also help increasing the consistency between the dynamic simulation results and the input parameters required for experiments. Results of the gait analysis show that the model can successfully reproduce the kinematics of the system joints derived from experiments. In addition, it is shown by dynamics analysis that WAMC provides a comfortable ride as the forces and torques acting on the system are in admissible limits.
{"title":"Improvement in modeling of Walking Assist Machine Using Crutches for dynamic analysis","authors":"Ekin Basalp, K. Hara, H. Yamaura, D. Matsuura, Y. Takeda","doi":"10.1109/ICAR.2015.7251493","DOIUrl":"https://doi.org/10.1109/ICAR.2015.7251493","url":null,"abstract":"In a previous study, a gait assistive device embodying actuators, known as Walking Assist Machine Using Crutches (WAMC), was proposed for people who suffer from lower limb disabilities. Experiments with healthy subjects show that WAMC can provide upright stance position and assisted forward gait to the user. However, the simplistic kinetostatic model used in gait analysis does not permit to obtain forces and torques acting on the system (user and WAMC) in detail. In this paper, an anthropometric 2D model which can investigate the gait characteristics of the system is proposed. Force and torques acting on the system parts can be guessed prior to the experiments if the user's height and weight are specified. This will also help increasing the consistency between the dynamic simulation results and the input parameters required for experiments. Results of the gait analysis show that the model can successfully reproduce the kinematics of the system joints derived from experiments. In addition, it is shown by dynamics analysis that WAMC provides a comfortable ride as the forces and torques acting on the system are in admissible limits.","PeriodicalId":432004,"journal":{"name":"2015 International Conference on Advanced Robotics (ICAR)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133881901","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 : 2015-07-27DOI: 10.1109/ICAR.2015.7251460
Ilknur Umay, B. Fidan, M. Yuce
Wireless capsule endoscopy (WCE) localization techniques have gained increasing popularity for medical diagnostics and treatments, particularly in gastro-intestinal (GI) track, in recent years. In these localization techniques, some parameters such as relative permittivity and path loss coefficients in the human body have significant effects on the accuracy of the capsule localization. Hence, these coefficients need to be accurately known or estimated for the effectiveness of the localization algorithm. This paper proposes a new adaptive biomedical capsule localization scheme utilizing a recent geometric cooperative sensor technique to estimate the path loss coefficient for received signal strength (RSS) and the relative permittivity for time-of-flight (TOF) based range sensors. This cooperative environmental coefficient estimation technique involves use of a mobile sensor triplet in place of a single sensor, and provides instantaneous estimates. The proposed capsule localization scheme is combination of a discrete time recursive least squares (RLS) based adaptive localization scheme and the aforementioned coefficient estimation technique, with design parameters specific for the particular WCE localization application. The accuracy and effectiveness of the proposed scheme is successfully demonstrated via a set of simulation tests.
{"title":"Endoscopic capsule localization with unknown signal propagation coefficients","authors":"Ilknur Umay, B. Fidan, M. Yuce","doi":"10.1109/ICAR.2015.7251460","DOIUrl":"https://doi.org/10.1109/ICAR.2015.7251460","url":null,"abstract":"Wireless capsule endoscopy (WCE) localization techniques have gained increasing popularity for medical diagnostics and treatments, particularly in gastro-intestinal (GI) track, in recent years. In these localization techniques, some parameters such as relative permittivity and path loss coefficients in the human body have significant effects on the accuracy of the capsule localization. Hence, these coefficients need to be accurately known or estimated for the effectiveness of the localization algorithm. This paper proposes a new adaptive biomedical capsule localization scheme utilizing a recent geometric cooperative sensor technique to estimate the path loss coefficient for received signal strength (RSS) and the relative permittivity for time-of-flight (TOF) based range sensors. This cooperative environmental coefficient estimation technique involves use of a mobile sensor triplet in place of a single sensor, and provides instantaneous estimates. The proposed capsule localization scheme is combination of a discrete time recursive least squares (RLS) based adaptive localization scheme and the aforementioned coefficient estimation technique, with design parameters specific for the particular WCE localization application. The accuracy and effectiveness of the proposed scheme is successfully demonstrated via a set of simulation tests.","PeriodicalId":432004,"journal":{"name":"2015 International Conference on Advanced Robotics (ICAR)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115676916","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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