Pub Date : 2012-12-24DOI: 10.1109/IROS.2012.6385623
A. Virta, Jaakko V. I. Timonen, Robin H. A. Ras, Quan Zhou
This paper proposes a sensing concept based on measuring the geometrical deformation of artificial magnetic cilia indirectly with a magnetoresistive sensor. The cilia are fabricated with a template-free method based on the evaporation of solvent from a suspension containing micron-sized magnetic particles and dissolved elastomeric polymers under constant magnetic field. The sensing concept has applications in e.g. flow measurement and tactile force sensing. A mathematical model for the magnetic field of the cilium is developed and experimental results are presented to verify the model.
{"title":"Force sensing using artificial magnetic cilia","authors":"A. Virta, Jaakko V. I. Timonen, Robin H. A. Ras, Quan Zhou","doi":"10.1109/IROS.2012.6385623","DOIUrl":"https://doi.org/10.1109/IROS.2012.6385623","url":null,"abstract":"This paper proposes a sensing concept based on measuring the geometrical deformation of artificial magnetic cilia indirectly with a magnetoresistive sensor. The cilia are fabricated with a template-free method based on the evaporation of solvent from a suspension containing micron-sized magnetic particles and dissolved elastomeric polymers under constant magnetic field. The sensing concept has applications in e.g. flow measurement and tactile force sensing. A mathematical model for the magnetic field of the cilium is developed and experimental results are presented to verify the model.","PeriodicalId":6358,"journal":{"name":"2012 IEEE/RSJ International Conference on Intelligent Robots and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75225681","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 : 2012-12-24DOI: 10.1109/IROS.2012.6386200
Eui-Jung Jung, B. Yi, S. Yuta
This paper presents tracking algorithms of a mobile robot that tracks a human in front. The mobile robot, which is a differential-driven wheel type, is equipped with a laser range finder to perform human tracking in front. Initially, we recommend the torso part for the robust tracking of the human body in outdoor environment by a laser range finder. To track a human in front, we define a virtual target determined by the velocity of the target human. For a more efficient movement of the mobile robot, a desired heading direction of the robot considering motion vectors of the robot and the human is proposed.
{"title":"Control algorithms for a mobile robot tracking a human in front","authors":"Eui-Jung Jung, B. Yi, S. Yuta","doi":"10.1109/IROS.2012.6386200","DOIUrl":"https://doi.org/10.1109/IROS.2012.6386200","url":null,"abstract":"This paper presents tracking algorithms of a mobile robot that tracks a human in front. The mobile robot, which is a differential-driven wheel type, is equipped with a laser range finder to perform human tracking in front. Initially, we recommend the torso part for the robust tracking of the human body in outdoor environment by a laser range finder. To track a human in front, we define a virtual target determined by the velocity of the target human. For a more efficient movement of the mobile robot, a desired heading direction of the robot considering motion vectors of the robot and the human is proposed.","PeriodicalId":6358,"journal":{"name":"2012 IEEE/RSJ International Conference on Intelligent Robots and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75767983","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 : 2012-12-24DOI: 10.1109/IROS.2012.6386121
Ryuma Niiyama
Pneumatic actuators have many attributes such as natural compliance and high peak power capabilities that make them attractive for research in dynamic legged locomotion. However, the effects of nonlinear flow through the pneumatic components limit the bandwidth of actuators, thus restricting their use in a high-performance control system. We believe that a model-based control design can overcome these bandwidth limitations. In this study, we demonstrate that black-box system identification of actuator dynamics can be effectively combined with nonlinear trajectory optimization and stabilization to accomplish dynamic tasks on underactuated robots. We present two case studies: an underactuated cart-pole system with the cart driven by a pneumatic actuator and a compass gait walking robot with pneumatic toes.
{"title":"Model-based trajectory control of robots with pneumatic actuator dynamics","authors":"Ryuma Niiyama","doi":"10.1109/IROS.2012.6386121","DOIUrl":"https://doi.org/10.1109/IROS.2012.6386121","url":null,"abstract":"Pneumatic actuators have many attributes such as natural compliance and high peak power capabilities that make them attractive for research in dynamic legged locomotion. However, the effects of nonlinear flow through the pneumatic components limit the bandwidth of actuators, thus restricting their use in a high-performance control system. We believe that a model-based control design can overcome these bandwidth limitations. In this study, we demonstrate that black-box system identification of actuator dynamics can be effectively combined with nonlinear trajectory optimization and stabilization to accomplish dynamic tasks on underactuated robots. We present two case studies: an underactuated cart-pole system with the cart driven by a pneumatic actuator and a compass gait walking robot with pneumatic toes.","PeriodicalId":6358,"journal":{"name":"2012 IEEE/RSJ International Conference on Intelligent Robots and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74546819","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 : 2012-12-24DOI: 10.1109/IROS.2012.6385699
T. Sugihara
A novel biped control is proposed. Since it doesn't require referential motion trajectories defined by time, it can achieve longitudinal walking which is flexible enough to follow an arbitrary referential velocity given at random timing and to cope with unexpected external forces. The controller is developed based on the dynamics morphing, which is a framework to enable seamless transitions between various motions by continuously morphing the dynamical structure of the feedback system. Thus, it is compatible with the standing, the stepping-out for emergency, and so forth. Three key techniques are (i) morphing from the standing stabilizer with a stable equilibrium point to the velocity-follower which lacks any equilibrium points, (ii) a foot control maneuver which is automatically activated together with the morphing into the velocity following control, and (iii) automatic update of the referential position of COM for safety when going back to the standing stabilization. Although it is based on the same principle with the simulated regulator proposed by the author, the proposed controller is advantageous to it as it doesn't require an additional automaton to update the referential position of COM. The idea was examined through interactive computer simulations.
{"title":"Biped control to follow arbitrary referential longitudinal velocity based on dynamics morphing","authors":"T. Sugihara","doi":"10.1109/IROS.2012.6385699","DOIUrl":"https://doi.org/10.1109/IROS.2012.6385699","url":null,"abstract":"A novel biped control is proposed. Since it doesn't require referential motion trajectories defined by time, it can achieve longitudinal walking which is flexible enough to follow an arbitrary referential velocity given at random timing and to cope with unexpected external forces. The controller is developed based on the dynamics morphing, which is a framework to enable seamless transitions between various motions by continuously morphing the dynamical structure of the feedback system. Thus, it is compatible with the standing, the stepping-out for emergency, and so forth. Three key techniques are (i) morphing from the standing stabilizer with a stable equilibrium point to the velocity-follower which lacks any equilibrium points, (ii) a foot control maneuver which is automatically activated together with the morphing into the velocity following control, and (iii) automatic update of the referential position of COM for safety when going back to the standing stabilization. Although it is based on the same principle with the simulated regulator proposed by the author, the proposed controller is advantageous to it as it doesn't require an additional automaton to update the referential position of COM. The idea was examined through interactive computer simulations.","PeriodicalId":6358,"journal":{"name":"2012 IEEE/RSJ International Conference on Intelligent Robots and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74869337","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 : 2012-12-24DOI: 10.1109/IROS.2012.6385607
Daniel Gutiérrez-Gómez, L. Puig, J. J. Guerrero
In the last years monocular SLAM has been widely used to obtain highly accurate maps and trajectory estimations of a moving camera. However, one of the issues of this approach is that, due to the impossibility of the depth being measured in a single image, global scale is not observable and scene and camera motion can only be recovered up to scale. This problem gets aggravated as we deal with larger scenes since it is more likely that scale drift arises between different map portions and their corresponding motion estimates. To compute the absolute scale we need to know some kind of dimension of the scene (e.g., actual size of an element of the scene, velocity of the camera or baseline between two frames) and somehow integrate it in the SLAM estimation. In this paper, we present a method to recover the scale of the scene using an omnidirectional camera mounted on a helmet. The high precision of visual SLAM allows the head vertical oscillation during walking to be perceived in the trajectory estimation. By performing a spectral analysis on the camera vertical displacement, we can measure the step frequency. We relate the step frequency to the speed of the camera by an empirical formula based on biomedical experiments on human walking. This speed measurement is integrated in a particle filter to estimate the current scale factor and the 3D motion estimation with its true scale. We evaluated our approach using image sequences acquired while a person walks. Our experiments show that the proposed approach is able to cope with scale drift.
{"title":"Full scaled 3D visual odometry from a single wearable omnidirectional camera","authors":"Daniel Gutiérrez-Gómez, L. Puig, J. J. Guerrero","doi":"10.1109/IROS.2012.6385607","DOIUrl":"https://doi.org/10.1109/IROS.2012.6385607","url":null,"abstract":"In the last years monocular SLAM has been widely used to obtain highly accurate maps and trajectory estimations of a moving camera. However, one of the issues of this approach is that, due to the impossibility of the depth being measured in a single image, global scale is not observable and scene and camera motion can only be recovered up to scale. This problem gets aggravated as we deal with larger scenes since it is more likely that scale drift arises between different map portions and their corresponding motion estimates. To compute the absolute scale we need to know some kind of dimension of the scene (e.g., actual size of an element of the scene, velocity of the camera or baseline between two frames) and somehow integrate it in the SLAM estimation. In this paper, we present a method to recover the scale of the scene using an omnidirectional camera mounted on a helmet. The high precision of visual SLAM allows the head vertical oscillation during walking to be perceived in the trajectory estimation. By performing a spectral analysis on the camera vertical displacement, we can measure the step frequency. We relate the step frequency to the speed of the camera by an empirical formula based on biomedical experiments on human walking. This speed measurement is integrated in a particle filter to estimate the current scale factor and the 3D motion estimation with its true scale. We evaluated our approach using image sequences acquired while a person walks. Our experiments show that the proposed approach is able to cope with scale drift.","PeriodicalId":6358,"journal":{"name":"2012 IEEE/RSJ International Conference on Intelligent Robots and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73013729","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 : 2012-12-24DOI: 10.1109/IROS.2012.6385706
Raymond Oung, M. P. Cruz, R. D’Andrea
Designing a controller that is scalable, robust, and that can adapt to an arbitrary configuration is one of the major challenges of modular robotics. This paper takes one step forward in addressing this challenge by presenting a methodology for controlling any flight-feasible configuration of a modular flying vehicle, in this case the Distributed Flight Array (DFA). In this work we present a well-structured, parameterized controller and describe a method for optimizing its parameters in order to achieve the best possible performance subject to the system's physical constraints. We then show how the configuration space of the DFA can be parameterized by only a few variables and propose a straightforward approach for mapping this configuration space to its control parameter space.
{"title":"A parameterized control methodology for a modular flying vehicle","authors":"Raymond Oung, M. P. Cruz, R. D’Andrea","doi":"10.1109/IROS.2012.6385706","DOIUrl":"https://doi.org/10.1109/IROS.2012.6385706","url":null,"abstract":"Designing a controller that is scalable, robust, and that can adapt to an arbitrary configuration is one of the major challenges of modular robotics. This paper takes one step forward in addressing this challenge by presenting a methodology for controlling any flight-feasible configuration of a modular flying vehicle, in this case the Distributed Flight Array (DFA). In this work we present a well-structured, parameterized controller and describe a method for optimizing its parameters in order to achieve the best possible performance subject to the system's physical constraints. We then show how the configuration space of the DFA can be parameterized by only a few variables and propose a straightforward approach for mapping this configuration space to its control parameter space.","PeriodicalId":6358,"journal":{"name":"2012 IEEE/RSJ International Conference on Intelligent Robots and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73021206","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 : 2012-12-24DOI: 10.1109/IROS.2012.6385632
Alban Laflaquière, S. Argentieri, Olivia Breysse, Stéphane Genet, B. Gas
Developmental Robotics offers a new approach to numerous AI features that are often taken as granted. Traditionally, perception is supposed to be an inherent capacity of the agent. Moreover, it largely relies on models built by the system's designer. A new approach is to consider perception as an experimentally acquired ability that is learned exclusively through the analysis of the agent's sensorimotor flow. Previous works, based on H.Poincaré's intuitions and the sensorimotor contingencies theory, allow a simulated agent to extract the dimension of geometrical space in which it is immersed without any a priori knowledge. Those results are limited to infinitesimal movement's amplitude of the system. In this paper, a non-linear dimension estimation method is proposed to push back this limitation.
{"title":"A non-linear approach to space dimension perception by a naive agent","authors":"Alban Laflaquière, S. Argentieri, Olivia Breysse, Stéphane Genet, B. Gas","doi":"10.1109/IROS.2012.6385632","DOIUrl":"https://doi.org/10.1109/IROS.2012.6385632","url":null,"abstract":"Developmental Robotics offers a new approach to numerous AI features that are often taken as granted. Traditionally, perception is supposed to be an inherent capacity of the agent. Moreover, it largely relies on models built by the system's designer. A new approach is to consider perception as an experimentally acquired ability that is learned exclusively through the analysis of the agent's sensorimotor flow. Previous works, based on H.Poincaré's intuitions and the sensorimotor contingencies theory, allow a simulated agent to extract the dimension of geometrical space in which it is immersed without any a priori knowledge. Those results are limited to infinitesimal movement's amplitude of the system. In this paper, a non-linear dimension estimation method is proposed to push back this limitation.","PeriodicalId":6358,"journal":{"name":"2012 IEEE/RSJ International Conference on Intelligent Robots and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75717109","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 : 2012-12-24DOI: 10.3182/20120905-3-HR-2030.00047
Y. Karayiannidis, Christian Smith, Petter Ögren, D. Kragic
The problem of door opening is fundamental for robots operating in domestic environments. Since these environments are generally less structured than industrial environments, several types of uncertainties associated with the dynamics and kinematics of a door must be dealt with to achieve successful opening. This paper proposes a method that can open doors without prior knowledge of the door kinematics. The proposed method can be implemented on a velocity-controlled manipulator with force sensing capabilities at the end-effector. The method consists of a velocity controller which uses force measurements and estimates of the radial direction based on adaptive estimates of the position of the door hinge. The control action is decomposed into an estimated radial and tangential direction following the concept of hybrid force/motion control. A force controller acting within the velocity controller regulates the radial force to a desired small value while the velocity controller ensures that the end effector of the robot moves with a desired tangential velocity leading to task completion. This paper also provides a proof that the adaptive estimates of the radial direction converge to the actual radial vector. The performance of the control scheme is demonstrated in both simulation and on a real robot.
{"title":"“Open sesame!” adaptive force/velocity control for opening unknown doors","authors":"Y. Karayiannidis, Christian Smith, Petter Ögren, D. Kragic","doi":"10.3182/20120905-3-HR-2030.00047","DOIUrl":"https://doi.org/10.3182/20120905-3-HR-2030.00047","url":null,"abstract":"The problem of door opening is fundamental for robots operating in domestic environments. Since these environments are generally less structured than industrial environments, several types of uncertainties associated with the dynamics and kinematics of a door must be dealt with to achieve successful opening. This paper proposes a method that can open doors without prior knowledge of the door kinematics. The proposed method can be implemented on a velocity-controlled manipulator with force sensing capabilities at the end-effector. The method consists of a velocity controller which uses force measurements and estimates of the radial direction based on adaptive estimates of the position of the door hinge. The control action is decomposed into an estimated radial and tangential direction following the concept of hybrid force/motion control. A force controller acting within the velocity controller regulates the radial force to a desired small value while the velocity controller ensures that the end effector of the robot moves with a desired tangential velocity leading to task completion. This paper also provides a proof that the adaptive estimates of the radial direction converge to the actual radial vector. The performance of the control scheme is demonstrated in both simulation and on a real robot.","PeriodicalId":6358,"journal":{"name":"2012 IEEE/RSJ International Conference on Intelligent Robots and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75722899","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 : 2012-12-24DOI: 10.1109/IROS.2012.6385631
S. Shimoda, Y. Yoshihara, K. Fujimoto, Takashi Yamamoto, Iwao Maeda, H. Kimura
Tacit learning is the novel learning scheme based on the principle of biological control to create the appropriate behaviors adapted to the environment. Signal accumulation is the key factor for tacit learning in the process of behavior adaptation. To clarify the role of the signal accumulation in the learning process, we analyzed it dividing into the two processes depending on the control speed. The fast process is used for the behavior control and the slow process is used for the behavior adaptation to the environment. We developed the continuous-time controller for tacit learning with the integrators and showed that the signal accumulation can estimate a part of the robot model through the interactions between the robot body and the environment. This capability of tacit learning is useful to control a plant where the modeling errors and model changes are the critical problems for the stable controls. As the prominent example of the control of such plant, we experimentally verified that tacit learning can create the bipedal walking gait that pushes the ground by the support leg at the moment of losing contact with the ground.
{"title":"Stability analysis of tacit learning based on environmental signal accumulation","authors":"S. Shimoda, Y. Yoshihara, K. Fujimoto, Takashi Yamamoto, Iwao Maeda, H. Kimura","doi":"10.1109/IROS.2012.6385631","DOIUrl":"https://doi.org/10.1109/IROS.2012.6385631","url":null,"abstract":"Tacit learning is the novel learning scheme based on the principle of biological control to create the appropriate behaviors adapted to the environment. Signal accumulation is the key factor for tacit learning in the process of behavior adaptation. To clarify the role of the signal accumulation in the learning process, we analyzed it dividing into the two processes depending on the control speed. The fast process is used for the behavior control and the slow process is used for the behavior adaptation to the environment. We developed the continuous-time controller for tacit learning with the integrators and showed that the signal accumulation can estimate a part of the robot model through the interactions between the robot body and the environment. This capability of tacit learning is useful to control a plant where the modeling errors and model changes are the critical problems for the stable controls. As the prominent example of the control of such plant, we experimentally verified that tacit learning can create the bipedal walking gait that pushes the ground by the support leg at the moment of losing contact with the ground.","PeriodicalId":6358,"journal":{"name":"2012 IEEE/RSJ International Conference on Intelligent Robots and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78247442","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 : 2012-12-24DOI: 10.1109/IROS.2012.6386073
Rohan Paul, Rudolph Triebel, D. Rus, P. Newman
This paper presents a novel semantic categorization method for 3D point cloud data using supervised, multiclass Gaussian Process (GP) classification. In contrast to other approaches, and particularly Support Vector Machines, which probably are the most used method for this task to date, GPs have the major advantage of providing informative uncertainty estimates about the resulting class labels. As we show in experiments, these uncertainty estimates can either be used to improve the classification by neglecting uncertain class labels or - more importantly - they can serve as an indication of the under-representation of certain classes in the training data. This means that GP classifiers are much better suited in a lifelong learning framework, where not all classes are represented initially, but instead new training data arrives during the operation of the robot.
{"title":"Semantic categorization of outdoor scenes with uncertainty estimates using multi-class gaussian process classification","authors":"Rohan Paul, Rudolph Triebel, D. Rus, P. Newman","doi":"10.1109/IROS.2012.6386073","DOIUrl":"https://doi.org/10.1109/IROS.2012.6386073","url":null,"abstract":"This paper presents a novel semantic categorization method for 3D point cloud data using supervised, multiclass Gaussian Process (GP) classification. In contrast to other approaches, and particularly Support Vector Machines, which probably are the most used method for this task to date, GPs have the major advantage of providing informative uncertainty estimates about the resulting class labels. As we show in experiments, these uncertainty estimates can either be used to improve the classification by neglecting uncertain class labels or - more importantly - they can serve as an indication of the under-representation of certain classes in the training data. This means that GP classifiers are much better suited in a lifelong learning framework, where not all classes are represented initially, but instead new training data arrives during the operation of the robot.","PeriodicalId":6358,"journal":{"name":"2012 IEEE/RSJ International Conference on Intelligent Robots and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80120839","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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