Articles de revista
http://hdl.handle.net/2117/22179
2024-03-29T05:38:55Z
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Eduquem les criatures... també les artificials!
http://hdl.handle.net/2117/403038
Eduquem les criatures... també les artificials!
Torras, Carme
Artificial és tot allò creat pels humans, ja siguin objectes d’artesania com enginys fruit de la tecnologia. Malgrat l’antiguitat dels productes artificials i de la utilització d’eines per construir-los, no és fins a principis del segle XX que filòsofs com Martin Heidegger comencen a reflexionar sobre el que anomenen “l’era de la tècnica”.
2024-02-23T12:38:15Z
Torras, Carme
Artificial és tot allò creat pels humans, ja siguin objectes d’artesania com enginys fruit de la tecnologia. Malgrat l’antiguitat dels productes artificials i de la utilització d’eines per construir-los, no és fins a principis del segle XX que filòsofs com Martin Heidegger comencen a reflexionar sobre el que anomenen “l’era de la tècnica”.
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Humans i robots: ¿qui modela qui?
http://hdl.handle.net/2117/402087
Humans i robots: ¿qui modela qui?
Torras, Carme
En un futur ben proper, els robots socials, que avui són objecte d’intensa investigació, sens dubte ens modelaran. Individualment i com a societat. Això ens obliga a preparar-nos per respondre moltes qüestions, principalment relacionades amb l’ètica.
2024-02-16T10:35:25Z
Torras, Carme
En un futur ben proper, els robots socials, que avui són objecte d’intensa investigació, sens dubte ens modelaran. Individualment i com a societat. Això ens obliga a preparar-nos per respondre moltes qüestions, principalment relacionades amb l’ètica.
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Gendered human–robot Interactions in services
http://hdl.handle.net/2117/400885
Gendered human–robot Interactions in services
Forgas Coll, Santiago; Huertas Garcia, Rubén; Andriella, Antonio; Alenyà Ribas, Guillem
The outbreak of Covid-19 precipitated the use of service robots in customer-facing services as a replacement for employ- ees to avoid human-to-human contact. However, this development has not resolved the debate as to whether robots should be characterized with gender attributes or simply be genderless. This study explores whether endowing a robot with gender attributes makes it more acceptable as a service provider among stated men and women. To this end, an experiment was conducted at a public fair in which a gendered robot simulated the provision of a service to customers, which consisted of offering them advice, hints, and messages of encouragement to help complete a eudaemonic puzzle. A parsimonious version of the Almere model was used to estimate acceptance of the technology. The findings reveal that for both stated men and women, the main drivers for accepting the female-coded robot are perceived usefulness and social influence, although women attach greater importance to social influence. For the male-coded robot, perceived usefulness and social influence are the main arguments for women, while for men they are enjoyment, perceived usefulness and, negatively, ease of use. In addition, different indirect effects between stated sexes are also identified. In summary, men and women consider different factors when accepting robots of each gender.
© The Author(s) 2023
2024-02-02T12:44:30Z
Forgas Coll, Santiago
Huertas Garcia, Rubén
Andriella, Antonio
Alenyà Ribas, Guillem
The outbreak of Covid-19 precipitated the use of service robots in customer-facing services as a replacement for employ- ees to avoid human-to-human contact. However, this development has not resolved the debate as to whether robots should be characterized with gender attributes or simply be genderless. This study explores whether endowing a robot with gender attributes makes it more acceptable as a service provider among stated men and women. To this end, an experiment was conducted at a public fair in which a gendered robot simulated the provision of a service to customers, which consisted of offering them advice, hints, and messages of encouragement to help complete a eudaemonic puzzle. A parsimonious version of the Almere model was used to estimate acceptance of the technology. The findings reveal that for both stated men and women, the main drivers for accepting the female-coded robot are perceived usefulness and social influence, although women attach greater importance to social influence. For the male-coded robot, perceived usefulness and social influence are the main arguments for women, while for men they are enjoyment, perceived usefulness and, negatively, ease of use. In addition, different indirect effects between stated sexes are also identified. In summary, men and women consider different factors when accepting robots of each gender.
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Shared task representation for human–robot collaborative navigation: the collaborative search case
http://hdl.handle.net/2117/395911
Shared task representation for human–robot collaborative navigation: the collaborative search case
Dalmasso Blanch, Marc; Domínguez Vidal, José Enrique; Torres Rodriguez, Ivan Jesús; Jiménez Schlegl, Pablo; Garrell Zulueta, Anais; Sanfeliu Cortés, Alberto
Recent research in Human Robot Collaboration (HRC) has spread and specialised in many sub-fields. Many show considerable advances, but the human–robot collaborative navigation (HRCN) field seems to be stuck focusing on implicit collaboration settings, on hypothetical or simulated task allocation problems, on shared autonomy or on having the human as a manager. This work takes a step forward by presenting an end-to-end system capable of handling real-world human–robot collaborative navigation tasks. This system makes use of the Social Reward Sources model (SRS), a knowledge representation to simultaneously tackle task allocation and path planning, proposes a multi-agent Monte Carlo Tree Search (MCTS) planner for human–robot teams, presents the collaborative search as a testbed for HRCN and studies the usage of smartphones for communication in this setting. The detailed experiments prove the viability of the approach, explore collaboration roles adopted by the human–robot team and test the acceptability and utility of different communication interface designs.
© The Author(s) 2023
2023-11-07T10:57:25Z
Dalmasso Blanch, Marc
Domínguez Vidal, José Enrique
Torres Rodriguez, Ivan Jesús
Jiménez Schlegl, Pablo
Garrell Zulueta, Anais
Sanfeliu Cortés, Alberto
Recent research in Human Robot Collaboration (HRC) has spread and specialised in many sub-fields. Many show considerable advances, but the human–robot collaborative navigation (HRCN) field seems to be stuck focusing on implicit collaboration settings, on hypothetical or simulated task allocation problems, on shared autonomy or on having the human as a manager. This work takes a step forward by presenting an end-to-end system capable of handling real-world human–robot collaborative navigation tasks. This system makes use of the Social Reward Sources model (SRS), a knowledge representation to simultaneously tackle task allocation and path planning, proposes a multi-agent Monte Carlo Tree Search (MCTS) planner for human–robot teams, presents the collaborative search as a testbed for HRCN and studies the usage of smartphones for communication in this setting. The detailed experiments prove the viability of the approach, explore collaboration roles adopted by the human–robot team and test the acceptability and utility of different communication interface designs.
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Condition-based design of variable impedance controllers from user demonstrations
http://hdl.handle.net/2117/394194
Condition-based design of variable impedance controllers from user demonstrations
San Miguel Tello, Alberto; Puig Cayuela, Vicenç; Alenyà Ribas, Guillem
This paper presents an approach to ensure conditions on Variable Impedance Controllers through the off-line tuning of the parameters involved in its description. In particular, we prove its application to term modulations defined by a Learning from Demonstration technique. This is performed through the assessment of conditions regarding safety and performance, which encompass heuristics and constraints in the form of Linear Matrix Inequalities. Latter ones allow to define a convex optimisation problem to analyse their fulfilment, and require a polytopic description of the VIC, in this case, obtained from its formulation as a discrete-time Linear Parameter Varying system. With respect to the current state-of-art, this approach only limits the term definition obtained by the Learning from Demonstration technique to be continuous and function of exogenous signals, i.e. external variables to the robot. Therefore, using a solution-search method, the most suitable set of parameters according to assessment criteria can be obtained. Using a 7-DoF KinovaGen3 manipulator, validation and comparison against solutions with relaxed conditions are performed. The method is applied to generate Variable Impedance Controllers for a pulley belt looping task, inspired by the Assembly Challenge for Industrial Robotics in World Robot Summit 2018, to reduce the exerted force with respect to a standard (constant) Impedance Controller. These controllers fulfil a set of safety constraints, namely stability, bounds on task variables and maximum response overshooting; and their performance is determined by the User Preference heuristic, which allows to intuitively define the desired compliant behaviour along the task. In the context of the task, this is used to generate new controllers for one-off modifications of the nominal belt looping task setup without new demonstrations.
2023-09-28T09:13:36Z
San Miguel Tello, Alberto
Puig Cayuela, Vicenç
Alenyà Ribas, Guillem
This paper presents an approach to ensure conditions on Variable Impedance Controllers through the off-line tuning of the parameters involved in its description. In particular, we prove its application to term modulations defined by a Learning from Demonstration technique. This is performed through the assessment of conditions regarding safety and performance, which encompass heuristics and constraints in the form of Linear Matrix Inequalities. Latter ones allow to define a convex optimisation problem to analyse their fulfilment, and require a polytopic description of the VIC, in this case, obtained from its formulation as a discrete-time Linear Parameter Varying system. With respect to the current state-of-art, this approach only limits the term definition obtained by the Learning from Demonstration technique to be continuous and function of exogenous signals, i.e. external variables to the robot. Therefore, using a solution-search method, the most suitable set of parameters according to assessment criteria can be obtained. Using a 7-DoF KinovaGen3 manipulator, validation and comparison against solutions with relaxed conditions are performed. The method is applied to generate Variable Impedance Controllers for a pulley belt looping task, inspired by the Assembly Challenge for Industrial Robotics in World Robot Summit 2018, to reduce the exerted force with respect to a standard (constant) Impedance Controller. These controllers fulfil a set of safety constraints, namely stability, bounds on task variables and maximum response overshooting; and their performance is determined by the User Preference heuristic, which allows to intuitively define the desired compliant behaviour along the task. In the context of the task, this is used to generate new controllers for one-off modifications of the nominal belt looping task setup without new demonstrations.
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Social robot-delivered customer-facing services: an assessment of the experience
http://hdl.handle.net/2117/393291
Social robot-delivered customer-facing services: an assessment of the experience
Forgas Coll, Santiago; Huertas Garcia, Rubén; Andriella, Antonio; Alenyà Ribas, Guillem
The ability to install social intelligence protocols in robots in order for them to exhibit conversational skills has made them ideal tools for delivering services with a high cognitive and low emotional load. Little is known about how this capability influences the customer experience and the intention to continue receiving these services. Experiences were assessed in a study simulating customer-facing service delivery, and the constructs of the technology readiness index and stated gender were analysed as possible moderators in a quasi-experiment. Hedonic quality was the most relevant factor explaining attitude, and attitude explained intention to use as well as social influence. As for the constructs of technological readiness and gender, optimism and innovativeness seem to be the most likely candidates for moderating the other variables. The most optimistic and the most innovative route would be for the main actors to continue adapting to social robot technology in the future.
2023-09-08T12:04:39Z
Forgas Coll, Santiago
Huertas Garcia, Rubén
Andriella, Antonio
Alenyà Ribas, Guillem
The ability to install social intelligence protocols in robots in order for them to exhibit conversational skills has made them ideal tools for delivering services with a high cognitive and low emotional load. Little is known about how this capability influences the customer experience and the intention to continue receiving these services. Experiences were assessed in a study simulating customer-facing service delivery, and the constructs of the technology readiness index and stated gender were analysed as possible moderators in a quasi-experiment. Hedonic quality was the most relevant factor explaining attitude, and attitude explained intention to use as well as social influence. As for the constructs of technological readiness and gender, optimism and innovativeness seem to be the most likely candidates for moderating the other variables. The most optimistic and the most innovative route would be for the main actors to continue adapting to social robot technology in the future.
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Generating predicate suggestions based on the space of plans: an example of planning with preferences
http://hdl.handle.net/2117/393058
Generating predicate suggestions based on the space of plans: an example of planning with preferences
Canal Camprodon, Gerard; Torras, Carme; Alenyà Ribas, Guillem
Task planning in human–robot environments tends to be particularly complex as it involves additional uncertainty introduced by the human user. Several plans, entailing few or various differences, can be obtained to solve the same given task. To choose among them, the usual least-cost plan criteria is not necessarily the best option, because here, human constraints and preferences come into play. Knowing these user preferences is very valuable to select an appropriate plan, but the preference values are usually hard to obtain. In this context, we propose the Space-of-Plans-based Suggestions (SoPS) algorithms that can provide suggestions for some planning predicates, which are used to define the state of the environment in a task planning problem where actions modify the predicates. We denote these predicates as suggestible predicates, of which user preferences are a particular case. The first algorithm is able to analyze the potential effect of the unknown predicates and provide suggestions to values for these unknown predicates that may produce better plans. The second algorithm is able to suggest changes to already known values that potentially improve the obtained reward. The proposed approach utilizes a Space of Plans Tree structure to represent a subset of the space of plans. The tree is traversed to find the predicates and the values that would most increase the reward, and output them as a suggestion to the user. Our evaluation in three preference-based assistive robotics domains shows how the proposed algorithms can improve task performance by suggesting the most effective predicate values first.
The version of record is available online at: https://dx.doi.org/10.1007/s11257-022-09327-w
2023-09-01T09:19:17Z
Canal Camprodon, Gerard
Torras, Carme
Alenyà Ribas, Guillem
Task planning in human–robot environments tends to be particularly complex as it involves additional uncertainty introduced by the human user. Several plans, entailing few or various differences, can be obtained to solve the same given task. To choose among them, the usual least-cost plan criteria is not necessarily the best option, because here, human constraints and preferences come into play. Knowing these user preferences is very valuable to select an appropriate plan, but the preference values are usually hard to obtain. In this context, we propose the Space-of-Plans-based Suggestions (SoPS) algorithms that can provide suggestions for some planning predicates, which are used to define the state of the environment in a task planning problem where actions modify the predicates. We denote these predicates as suggestible predicates, of which user preferences are a particular case. The first algorithm is able to analyze the potential effect of the unknown predicates and provide suggestions to values for these unknown predicates that may produce better plans. The second algorithm is able to suggest changes to already known values that potentially improve the obtained reward. The proposed approach utilizes a Space of Plans Tree structure to represent a subset of the space of plans. The tree is traversed to find the predicates and the values that would most increase the reward, and output them as a suggestion to the user. Our evaluation in three preference-based assistive robotics domains shows how the proposed algorithms can improve task performance by suggesting the most effective predicate values first.
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A representation of cloth states based on a derivative of the Gauss linking integral
http://hdl.handle.net/2117/392223
A representation of cloth states based on a derivative of the Gauss linking integral
Coltraro, Franco; Fontana, Josep; Amorós Torrent, Jaume; Alberich Carramiñana, Maria; Borràs Sol, Júlia; Torras, Carme
Robotic manipulation of cloth is a complex task because of the infinite-dimensional shape-state space of textiles, which makes their state estimation very difficult. In this paper we introduce the dGLI Cloth Coordinates, a finite low-dimensional representation of cloth states that allows us to efficiently distinguish a large variety of different folded states, opening the door to efficient learning methods for cloth manipulation planning and control. Our representation is based on a directional derivative of the Gauss Linking Integral and allows us to represent spatial as well as planar folded configurations in a consistent and unified way. The proposed dGLI Cloth Coordinates are shown to be more accurate in the representation of cloth states and significantly more sensitive to changes in grasping affordances than other classic shape distance methods. Finally, we apply our representation to real images of a cloth, showing that with it we can identify the different states using a distance-based classifier.
2023-07-26T06:51:11Z
Coltraro, Franco
Fontana, Josep
Amorós Torrent, Jaume
Alberich Carramiñana, Maria
Borràs Sol, Júlia
Torras, Carme
Robotic manipulation of cloth is a complex task because of the infinite-dimensional shape-state space of textiles, which makes their state estimation very difficult. In this paper we introduce the dGLI Cloth Coordinates, a finite low-dimensional representation of cloth states that allows us to efficiently distinguish a large variety of different folded states, opening the door to efficient learning methods for cloth manipulation planning and control. Our representation is based on a directional derivative of the Gauss Linking Integral and allows us to represent spatial as well as planar folded configurations in a consistent and unified way. The proposed dGLI Cloth Coordinates are shown to be more accurate in the representation of cloth states and significantly more sensitive to changes in grasping affordances than other classic shape distance methods. Finally, we apply our representation to real images of a cloth, showing that with it we can identify the different states using a distance-based classifier.
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Enhancing egocentric 3D pose estimation with third person views
http://hdl.handle.net/2117/387921
Enhancing egocentric 3D pose estimation with third person views
Dhamanaskar, Ameya; Dimiccoli, Mariella; Corona Puyane, Enric; Pumarola Peris, Albert; Moreno-Noguer, Francesc
We propose a novel approach to enhance the 3D body pose estimation of a person computed from videos captured from a single wearable camera. The main technical contribution consists of leveraging high-level features linking first- and third-views in a joint embedding space. To learn such embedding space we introduce First2Third-Pose, a new paired synchronized dataset of nearly 2000 videos depicting human activities captured from both first- and third-view perspectives. We explicitly consider spatial- and motion-domain features, combined using a semi-Siamese architecture trained in a self-supervised fashion. Experimental results demonstrate that the joint multi-view embedded space learned with our dataset is useful to extract discriminatory features from arbitrary single-view egocentric videos, with no need to perform any sort of domain adaptation or knowledge of camera parameters. An extensive evalu- ation demonstrates that we achieve significant improvement in egocentric 3D body pose estimation per- formance on two unconstrained datasets, over three supervised state-of-the-art approaches. The collected dataset and pre-trained model are available for research purposes.
© 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND
2023-05-26T11:03:16Z
Dhamanaskar, Ameya
Dimiccoli, Mariella
Corona Puyane, Enric
Pumarola Peris, Albert
Moreno-Noguer, Francesc
We propose a novel approach to enhance the 3D body pose estimation of a person computed from videos captured from a single wearable camera. The main technical contribution consists of leveraging high-level features linking first- and third-views in a joint embedding space. To learn such embedding space we introduce First2Third-Pose, a new paired synchronized dataset of nearly 2000 videos depicting human activities captured from both first- and third-view perspectives. We explicitly consider spatial- and motion-domain features, combined using a semi-Siamese architecture trained in a self-supervised fashion. Experimental results demonstrate that the joint multi-view embedded space learned with our dataset is useful to extract discriminatory features from arbitrary single-view egocentric videos, with no need to perform any sort of domain adaptation or knowledge of camera parameters. An extensive evalu- ation demonstrates that we achieve significant improvement in egocentric 3D body pose estimation per- formance on two unconstrained datasets, over three supervised state-of-the-art approaches. The collected dataset and pre-trained model are available for research purposes.
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Household cloth object set: fostering benchmarking in deformable object manipulation
http://hdl.handle.net/2117/384037
Household cloth object set: fostering benchmarking in deformable object manipulation
Garcia Camacho, Irene; Borràs Sol, Júlia; Calli, Berk; Norton, Adam; Alenyà Ribas, Guillem
Benchmarking of robotic manipulations is one of the open issues in robotic research. An important factor that has enabled progress in this area in the last decade is the existence of common object sets that have been shared among different research groups. However, the existing object sets are very limited when it comes to cloth-like objects that have unique particularities and challenges. This paper is a first step towards the design of a cloth object set to be distributed among research groups from the robotics cloth manipulation community. We present a set of household cloth objects and related tasks that serve to expose the challenges related to gathering such an object set and propose a roadmap to the design of common benchmarks in cloth manipulation tasks, with the intention to set the grounds for a future debate in the community that will be necessary to foster benchmarking for the manipulation of cloth-like objects. Some RGB-D and object scans are collected as examples for the objects in relevant configurations and shared in http://www.iri.upc.edu/groups/perception/ClothObjectSet/
© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
2023-02-23T11:59:20Z
Garcia Camacho, Irene
Borràs Sol, Júlia
Calli, Berk
Norton, Adam
Alenyà Ribas, Guillem
Benchmarking of robotic manipulations is one of the open issues in robotic research. An important factor that has enabled progress in this area in the last decade is the existence of common object sets that have been shared among different research groups. However, the existing object sets are very limited when it comes to cloth-like objects that have unique particularities and challenges. This paper is a first step towards the design of a cloth object set to be distributed among research groups from the robotics cloth manipulation community. We present a set of household cloth objects and related tasks that serve to expose the challenges related to gathering such an object set and propose a roadmap to the design of common benchmarks in cloth manipulation tasks, with the intention to set the grounds for a future debate in the community that will be necessary to foster benchmarking for the manipulation of cloth-like objects. Some RGB-D and object scans are collected as examples for the objects in relevant configurations and shared in http://www.iri.upc.edu/groups/perception/ClothObjectSet/