2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015
In general, the problems of objects' and rooms' categorizations for robotic appli... more In general, the problems of objects' and rooms' categorizations for robotic applications have been addressed separately. The current trend is, however, towards a joint modelling of both issues in order to leverage their mutual contextual relations: object -> room (e.g. the detection of a microwave indicates that the room is likely to be a kitchen), and room -> object (e.g. if the robot is in a bathroom, it is probable to nd a toilet). Probabilistic Graphical Models (PGMs) are typically employed to conveniently cope with such relations, relying on inference processes to hypothesize about objects' and rooms' categories. In this work we present a Conditional Random Field (CRF) model, a particular type of PGM, to jointly categorize objects and rooms from RGBD images exploiting object-object and object-room relations. The learning phase of the proposed CRF uses Human Knowledge (HK) to eliminate the necessity of gathering real training data. Concretely, HK is acquired through elicitation and codied into an ontology, which is exploited to effortless generate an arbitrary number of representative synthetic samples for training. The performance of the proposed CRF model has been assessed using the NYU2 dataset, achieving a success of 70% categorizing both, objects and rooms.
2015 European Conference on Mobile Robots (ECMR), 2015
In this work we present the Object Labeling Toolkit (OLT), a set of software components publicly ... more In this work we present the Object Labeling Toolkit (OLT), a set of software components publicly available for helping in the management and labeling of sequential RGB-D observations collected by a mobile robot. Such a robot can be equipped with an arbitrary number of RGB-D devices, possibly integrating other sensors (e.g. odometry, 2D laser scanners, etc.). OLT first merges the robot observations to generate a 3D reconstruction of the scene from which object segmentation and labeling is conveniently accomplished. The annotated labels are automatically propagated by the toolkit to each RGB-D observation in the collected sequence, providing a dense labeling of both intensity and depth images. The resulting objects' labels can be exploited for many robotic oriented applications, including high-level decision making, semantic mapping, or contextual object recognition. Software components within OLT are highly customizable and expandable, facilitating the integration of already-developed algorithms. To illustrate the toolkit suitability, we describe its application to robotic RGB-D sequences taken in a home environment.
This article addresses the problem of mobile robot localization using Ultra-Wide-Band (UWB) range... more This article addresses the problem of mobile robot localization using Ultra-Wide-Band (UWB) range measurements. UWB is a radio technology widely used for communications, that is recently receiving increasing attention for positioning applications. In these cases, the position of a mobile transceiver is determined from the distances to a set of fixed, well-localized beacons. Though this is a well-known problem in the scientific literature (the trilateration problem), the peculiarities of UWB range measurements (basically, distance errors and multipath effects) demand a different treatment to other similar solutions, as for example, those based on laser. This work presents a thorough experimental characterization of UWB ranges within a variety of environments and situations. From these experiments, we derive a probabilistic model which is then used by a particle filter to combine different readings from UWB beacons as well as the vehicle odometry. To account for the possible offset error due to multipath effects, the state tracked by the particle filter includes the offset of each beacon in addition to the planar robot pose (x,y,ϕ)(x,y,ϕ), both estimated sequentially. We show navigation results for a robot moving in indoor scenarios covered by three UWB beacons that validate our proposal.
GPS receivers are satellite-based devices widely used for vehicle localization that, given their ... more GPS receivers are satellite-based devices widely used for vehicle localization that, given their limitations, are not suitable for performing within indoor or dense urban environments. On the other hand, Ultra-Wide Band (UWB), a technology used for efficient wireless communication, has recently being used for vehicle localization in indoor environments with promising results. This paper focuses on the combination of both technologies for accurate positioning of vehicles
This paper describes a robotic wheelchair called SENA. It is based on a commercial powered wheelc... more This paper describes a robotic wheelchair called SENA. It is based on a commercial powered wheelchair which has been endowed with several sensors and devices managed by an onboard laptop. The sensorial system of SENA entails a proximity laser scanner, a ring of infrared sensors, a camera mounted on a pan&tilt unit, and two rotating sonars. SENA is a long-term project aimed to cover the requirements needed to perform in daily indoor environments. Some experiences of the use of our robotic wheelchair are also described at the end of the paper
This paper describes SANCHO, a mobile robot intended to perform within crowded areas as a servant... more This paper describes SANCHO, a mobile robot intended to perform within crowded areas as a servant, for instance as a fair or congress host. This robot has been constructed upon a commercial platform on which a number of sensors and devices have been integrated. A software control architecture has been implemented and adapted to this particular robot, enabling it to perform in human scenarios. Among the different subsystems of the control architecture developed for SANCHO, we highlight in this paper two of the most relevant ones: the navigation component which permits the robot to navigate in a safe and robust manner within crowded and dynamic environments, and the communication component which provides different possibilities for human-robot interaction. We illustrate the performance of SANCHO through a number of experiences carried out in public shows.
... 309-322, 2004. 5. Fong TW and Thorpe C. Robot as Partner: Vehicle Teleoperation with Collabor... more ... 309-322, 2004. 5. Fong TW and Thorpe C. Robot as Partner: Vehicle Teleoperation with Collaborative Control,Proc. of the NRL Workshop on Multi-Robot Systems, 2002. Page 11. ... 10. Kaelbling LP, Littman ML, Moore AW Reinforcement Learning: A Survey. ...
In this paper we consider the problem of creating a spatial representation of a gas distribution ... more In this paper we consider the problem of creating a spatial representation of a gas distribution in an environment using a mobile robot equipped with gas sensors. The gas distribution mapping method used models the information content of a given measurement about the average concentration distribution with respect to the point of measurement. In this paper, we present an extension which can consider the uncertainty about the robot's position in the gas distribution mapping. We present a preliminary result where a mobile robot equipped with gas sensors creates a map of a large indoor environment, using both spatial and olfactory information.
a b s t r a c t LEGO Mindstorms NXT robots are being increasingly used in undergraduate courses, ... more a b s t r a c t LEGO Mindstorms NXT robots are being increasingly used in undergraduate courses, mostly in roboticsrelated subjects. But other engineering topics, like the ones found in data acquisition, control and realtime subjects, also have difficult concepts that can be well understood only with good lab exercises. Such exercises require physical educational tools that should be low cost, easy to configure and use, multipurpose and motivational for the students, being all of this hard to achieve with a single device. The "classical" solution has been to acquire specific commercial kits for each subject, or even topic, usually proprietary and expensive. Our work extends the already existing alternative of using the LEGO Mindstorms NXT robots as a training platform, but not by imitating the same approach of commercial kits (e.g., to isolate some part of the robot for teaching a particular topic); we rather aim at accomplishing all the mentioned requirements simultaneously. For that purpose, we have used only one out-of-the-box, complete robot configuration, to be shared among different subjects without hardware/software/firmware modifications. This has reduced significantly the effort of a group of professors when preparing exercises, and encouraged the reuse of their work among several topics and subjects. Also, we have collected a number of surveys on students and the professors' experiences. In this paper we describe our approach and present in detail the results, which assess the higher motivational adequacy of using a complete robot in these subjects and also the real fulfillment of the other requirements along several academic years.
2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015
In general, the problems of objects' and rooms' categorizations for robotic appli... more In general, the problems of objects' and rooms' categorizations for robotic applications have been addressed separately. The current trend is, however, towards a joint modelling of both issues in order to leverage their mutual contextual relations: object -> room (e.g. the detection of a microwave indicates that the room is likely to be a kitchen), and room -> object (e.g. if the robot is in a bathroom, it is probable to nd a toilet). Probabilistic Graphical Models (PGMs) are typically employed to conveniently cope with such relations, relying on inference processes to hypothesize about objects' and rooms' categories. In this work we present a Conditional Random Field (CRF) model, a particular type of PGM, to jointly categorize objects and rooms from RGBD images exploiting object-object and object-room relations. The learning phase of the proposed CRF uses Human Knowledge (HK) to eliminate the necessity of gathering real training data. Concretely, HK is acquired through elicitation and codied into an ontology, which is exploited to effortless generate an arbitrary number of representative synthetic samples for training. The performance of the proposed CRF model has been assessed using the NYU2 dataset, achieving a success of 70% categorizing both, objects and rooms.
2015 European Conference on Mobile Robots (ECMR), 2015
In this work we present the Object Labeling Toolkit (OLT), a set of software components publicly ... more In this work we present the Object Labeling Toolkit (OLT), a set of software components publicly available for helping in the management and labeling of sequential RGB-D observations collected by a mobile robot. Such a robot can be equipped with an arbitrary number of RGB-D devices, possibly integrating other sensors (e.g. odometry, 2D laser scanners, etc.). OLT first merges the robot observations to generate a 3D reconstruction of the scene from which object segmentation and labeling is conveniently accomplished. The annotated labels are automatically propagated by the toolkit to each RGB-D observation in the collected sequence, providing a dense labeling of both intensity and depth images. The resulting objects' labels can be exploited for many robotic oriented applications, including high-level decision making, semantic mapping, or contextual object recognition. Software components within OLT are highly customizable and expandable, facilitating the integration of already-developed algorithms. To illustrate the toolkit suitability, we describe its application to robotic RGB-D sequences taken in a home environment.
This article addresses the problem of mobile robot localization using Ultra-Wide-Band (UWB) range... more This article addresses the problem of mobile robot localization using Ultra-Wide-Band (UWB) range measurements. UWB is a radio technology widely used for communications, that is recently receiving increasing attention for positioning applications. In these cases, the position of a mobile transceiver is determined from the distances to a set of fixed, well-localized beacons. Though this is a well-known problem in the scientific literature (the trilateration problem), the peculiarities of UWB range measurements (basically, distance errors and multipath effects) demand a different treatment to other similar solutions, as for example, those based on laser. This work presents a thorough experimental characterization of UWB ranges within a variety of environments and situations. From these experiments, we derive a probabilistic model which is then used by a particle filter to combine different readings from UWB beacons as well as the vehicle odometry. To account for the possible offset error due to multipath effects, the state tracked by the particle filter includes the offset of each beacon in addition to the planar robot pose (x,y,ϕ)(x,y,ϕ), both estimated sequentially. We show navigation results for a robot moving in indoor scenarios covered by three UWB beacons that validate our proposal.
GPS receivers are satellite-based devices widely used for vehicle localization that, given their ... more GPS receivers are satellite-based devices widely used for vehicle localization that, given their limitations, are not suitable for performing within indoor or dense urban environments. On the other hand, Ultra-Wide Band (UWB), a technology used for efficient wireless communication, has recently being used for vehicle localization in indoor environments with promising results. This paper focuses on the combination of both technologies for accurate positioning of vehicles
This paper describes a robotic wheelchair called SENA. It is based on a commercial powered wheelc... more This paper describes a robotic wheelchair called SENA. It is based on a commercial powered wheelchair which has been endowed with several sensors and devices managed by an onboard laptop. The sensorial system of SENA entails a proximity laser scanner, a ring of infrared sensors, a camera mounted on a pan&tilt unit, and two rotating sonars. SENA is a long-term project aimed to cover the requirements needed to perform in daily indoor environments. Some experiences of the use of our robotic wheelchair are also described at the end of the paper
This paper describes SANCHO, a mobile robot intended to perform within crowded areas as a servant... more This paper describes SANCHO, a mobile robot intended to perform within crowded areas as a servant, for instance as a fair or congress host. This robot has been constructed upon a commercial platform on which a number of sensors and devices have been integrated. A software control architecture has been implemented and adapted to this particular robot, enabling it to perform in human scenarios. Among the different subsystems of the control architecture developed for SANCHO, we highlight in this paper two of the most relevant ones: the navigation component which permits the robot to navigate in a safe and robust manner within crowded and dynamic environments, and the communication component which provides different possibilities for human-robot interaction. We illustrate the performance of SANCHO through a number of experiences carried out in public shows.
... 309-322, 2004. 5. Fong TW and Thorpe C. Robot as Partner: Vehicle Teleoperation with Collabor... more ... 309-322, 2004. 5. Fong TW and Thorpe C. Robot as Partner: Vehicle Teleoperation with Collaborative Control,Proc. of the NRL Workshop on Multi-Robot Systems, 2002. Page 11. ... 10. Kaelbling LP, Littman ML, Moore AW Reinforcement Learning: A Survey. ...
In this paper we consider the problem of creating a spatial representation of a gas distribution ... more In this paper we consider the problem of creating a spatial representation of a gas distribution in an environment using a mobile robot equipped with gas sensors. The gas distribution mapping method used models the information content of a given measurement about the average concentration distribution with respect to the point of measurement. In this paper, we present an extension which can consider the uncertainty about the robot's position in the gas distribution mapping. We present a preliminary result where a mobile robot equipped with gas sensors creates a map of a large indoor environment, using both spatial and olfactory information.
a b s t r a c t LEGO Mindstorms NXT robots are being increasingly used in undergraduate courses, ... more a b s t r a c t LEGO Mindstorms NXT robots are being increasingly used in undergraduate courses, mostly in roboticsrelated subjects. But other engineering topics, like the ones found in data acquisition, control and realtime subjects, also have difficult concepts that can be well understood only with good lab exercises. Such exercises require physical educational tools that should be low cost, easy to configure and use, multipurpose and motivational for the students, being all of this hard to achieve with a single device. The "classical" solution has been to acquire specific commercial kits for each subject, or even topic, usually proprietary and expensive. Our work extends the already existing alternative of using the LEGO Mindstorms NXT robots as a training platform, but not by imitating the same approach of commercial kits (e.g., to isolate some part of the robot for teaching a particular topic); we rather aim at accomplishing all the mentioned requirements simultaneously. For that purpose, we have used only one out-of-the-box, complete robot configuration, to be shared among different subjects without hardware/software/firmware modifications. This has reduced significantly the effort of a group of professors when preparing exercises, and encouraged the reuse of their work among several topics and subjects. Also, we have collected a number of surveys on students and the professors' experiences. In this paper we describe our approach and present in detail the results, which assess the higher motivational adequacy of using a complete robot in these subjects and also the real fulfillment of the other requirements along several academic years.
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Papers by Cipriano Galindo