Angel Pascual del Pobil Ferré

Do individual differences in dispositional behavioral tendencies, such as immersive tendency and need to belong, play a significant role in human-robot interaction? To answer this question, the present study conducted a 2 x 2 between-subjects experiment to examine the effects of immersive tendency (high vs. low) and need to belong (high vs. low) on individuals' perceptions of a social robot. Preliminary data analyses revealed that participants with a higher level of immersive tendency and need to belong showed greater attachment and trust towards the robot, and were more satisfied with their relationship with the robot than participants with a lower level of immersive tendency and need to belong. In addition, participants with a higher level of immersive tendency experienced greater feelings of social presence. Implications of notable findings are discussed.

Although telerobotic systems are becoming more complex, there are few actions they can perform on their own and, moreover, knowledge about the tasks they are being used for often relies only on their operator. In this paper, we present the design of a telerobotic system that features learning capabilities, can accept commands given in natural language and provides control of a generic vision-guided robot. This system is composed of a set of functional blocks that communicate among them according to the CORBA standard over an Internet-based network. Knowledge is originated from interaction with users and is stored in a shared database. The user interface translates user commands into a set of predefined commands that the robot controller can understand, making it unnecessary for users to know which particular robot they are working with. We describe the design of this system and focus on two of its main components: the user interface and the robot controller.

Is repeated exposure to banner ads more effective in facilitating interactions between consumers and advertised products? Does it work for everyone? To answer these questions, the present study conducted a 2 × 2 between-subjects experiment, and examined the relationship between ad exposure frequency and product knowledge as well as their effects on purchase intention and ad recall. Results indicated that more frequent exposure to banner ad and greater product knowledge had positive effects on purchase intention and ad recall. More interestingly, exposure frequency affected purchase intention and ad recall only for consumers with low product knowledge, but not for those with high product knowledge. Theoretical and practical implications of notable findings are discussed.

In this paper we address the problem of detecting contacts between a robot hand and an object during the approach and execution phases of manipulation tasks as a complement of touch perception. The motion produced on objects by unnoticed contacts is exploited to trigger the contact localization. Our method combines robot motion with tracking of target objects by means of point cloud to probabilistically estimate the location of contacts on a occupancy grid map. No previous knowledge on the object shape is required. The proposed approach is implemented on a real platform and experimentally validated in several cases.

Despite the increasing mutual interest between robotics and neuroscience research, the lack of a common language limits the interaction of the two fields. We propose a framework for facilitating such interaction, through the intro- duction of a tool designed to make robotic experiments more accessible to neuroscientists. Our proposal builds on two main components: a computational architecture to model brain activity at the functional level, and an interface that visualizes the activity of modeled areas on brain images, as in fMRI experiments. In order to test our tool and give a first example of the potentialities of the proposed platform, we introduce a model of the neural mechanisms for the extraction of relevant visual features and their mapping to hand configurations during the planning of grasping actions. I. I NTRODUCTION Interdisciplinary research involving high technology fields and life sciences is getting nowadays more and more common. Artificial intelligence has been from its very foundation a meeting-place for scientists of seemingly unrelated disciplines. Two such disciplines which met thanks to artificial intelligence are robotics and neuroscience, and although their encounter is producing very interesting developments (1), fundamental differences in research goals, methodologies and language prevent a more proficuous collaboration. Our research aims at facilitating the mutual enrichment and the communication between the two fields. One key issue is the choice of the proper level of abstraction for allowing the meaningful application of brain data on a robotic setup. We believe that the focus should be put on an intermediate, functional level. This has not yet been investigated as thor- oughly as the cellular level on the one hand and the behavioral level on the other, for its inherent complexity and speculative nature. In fact, neuroscientists rarely hazard to draw from their experiments implications which include complex interconnec- tions of several brain areas, whilst biologically-inspired robotic applications usually adopt solutions which allow to implement advanced skills with a limited effort. The framework we propose presents two characterizing components. The former feature of our proposal is a struc- tural approach to computational neuroscience models. First of all, models need to be applicable to robotic setups while maintaining a strong functional resemblance with brain areas. Moreover, they should be provided with the flexibility neces- sary for simulating different behaviors and skills through re- configuration, and not through re-programming. Only in this way can they be used to test theories and assumptions. In our view, this goal can be achieved using a distributed architecture of interconnected modules, which have to be simple and robust in order to allow easy modification of the data flow. The latter feature is the innovative interface fRI (functional Robotic Imaging) which associates each task performed by the robot to a brain area and visualizes its activation on a brain image, similarly to what happens in fMRI (functional Magnetic Resonance Imaging) experiments. The information flow can thus be monitored at very high level, and especially non-roboticists can benefit from this kind of functional vi- sualization. The scanning of the "robot brain" is much easier, faster and cheaper than real imaging, and far from representing an alternative to real experiments, it may help researchers in two important ways. First, fRI can be used to check in ad- vance the appropriateness of experimental protocols, reducing the expensive and complicate preliminary tests with human subjects (2). Second, it represents a way for comparing, and validate, possible explanations of experimental results deriving from different models. We believe that our tool may constitute a companion for neuroscientists for both the definition of experimental protocols and interpretation of results according to alternative models. Moreover, the rigorous model design is likely to represent an ideal inspiration source for planning completely new experiments. In the second part of this paper, we describe the outline of a functional model of the brain mechanisms responsible for the human abilities in the planning of vision-based grasping actions. The model rests mainly on human physiology, and has been conceived to be applied on a robotic setup. Thus, the design of the different modules and brain areas has been performed taking into account not only biological plausibility, but also practical issues related to engineering constraints. The part of the model dedicated to the extraction and mapping of visual features to hand configurations for grasping purposes will be used as a first testbed for showing how the fRI instrument works, and how it can constitute and additional, important tool for depicting the functioning of a relatively complex neural model. The paper is organized as follows. In the next…

This workshop will address the impact of robot morphology on HRI from the perspective of Interaction Science, which encompasses theory and design of human interaction with technology. Anthropomorphic designs, which are common, have to be balanced with the "uncanny valley effect," since different morphologies suggest different affordances to users, triggering a variety of cognitive heuristics and thereby shaping their interactions with robots. We expect progress towards more human-acceptable interactions with robots by understanding the cognitive, behavioral, organizational, and contextual factors of morphology in HRI, as well as new meta-theories and design guidelines. We emphasize a highly multi-disciplinary approach, by involving participants from social sciences, engineering, and design. Topics of presentation include but not limited to: Engineering considerations in designing robot morphology Empirical psychological considerations in designing robot morphology Aesthetic parameters for transcending the uncanny valley effect (UVE) with static, dynamic and interactive robots Physiological (fMRI) bases of UVE Cognitive heuristics triggered by morphological cues on robot interfaces Adaptation for multimodal robot interfaces Cognitive Robotic Engine for Dependable HRI Acceptance of Socially Interactive Robots Evaluation frameworks for human-like robots Robot appearances for social interactions among Autistic children

Abstract A key issue in robotics is the development of the ability to grasp unknown objects. This ability requires a grasp determination mechanism that, based on the analysis of the description of the object, determines how it can be stably grasped. In this paper, a grasp ...

Abstract Practical robot motion planning for multiple moving objects in complex scenarios requires very fast collision detection. The efficiency of the algorithms is critically dependent on the representation that is used to model the objects. We present a hierarchical spatial ...

Page 1. Brain Mechanisms for Robotic Object Pose Estimation Eris Chinellato, Beata J. Grzyb and Angel P. del Pobil Abstract—Integration of multiple visual cues provides nat-ural systems with superior abilities in dealing with nearby objects. ...

We present a practical method for coordinating two robots that have to move in close proximity. Few results have been reported in the literature for practical situations under time constraints. In addition, no previous approaches deal with the problem of coordinated ...

Localización: VI Encuentros de Geometría Computacional: Barcelona, 5-6-7 de julio de 1995, Departament de Matemàtica Aplicada II, Universitat Politècnica de Catalunya: Actas/coord. por Marc Noy Serrano, Carlos Seara, Mercé Claverol, M. del Roser Guardia ...

Localización: VI Encuentros de Geometría Computacional: Barcelona, 5-6-7 de julio de 1995, Departament de Matemàtica Aplicada II, Universitat Politècnica de Catalunya: Actas/coord. por Marc Noy Serrano, Carlos Seara, Mercé Claverol, M. del Roser Guardia ...

The paper presents a general object representation for efficient collision detection. Spatial representation is a crucial factor when motion planning is applied to real environments with complex objects, since the efficiency of the collision detection algorithms depends on the spatial representation used for the agents and obstacles in the scene. Our spatial model consists of a hierarchy of representations that

Robot motion planning deals with the ability of robots to plot their own collision-free motion. Recent research emphasis has been focused on developing practical motion planners for real manipulator arms with direct industrial relevance. This book concentrates on practical ...

... Iiiesta. Computing contact stabil-ity grasps of unknown objects by means of vision. In Helder Coelho, editor, IBERAMIA '98 Confer-ence, pages 241-252, Lisbon, Portugal, October 1998. P. J. Sanz, J. M. Iiiesta, and A. P. del Pobil. ...

... be able to locate the object, possibly identify it, use an appropriate strategy to find a stable ... As the only unknown quantity is the distance to the point being imaged, the Jacobians for ... a convenient input, the features delivered by the above module, the two best grasping points over ...

Abstract A key issue in robotics is the development of the ability to grasp unknown objects. This ability requires a grasp determination mechanism that, based on the analysis of the description of the object, determines how it can be stably grasped. In this paper, a grasp ...

Page 1. Proceedings of the 1996 IEEE International Conference on Robotics and Automation Minneapolis, Minnesota - April 1996 A Practical Approach to Collision Detection Between General Objects Angel P. del Pobil Miguel Pkrez Begoiia Martinez ...

Performance Evaluation and Benchmarking of Intelligent Systems presents research dedicated to the subject of performance evaluation and benchmarking of intelligent systems by drawing from the experiences and insights of leading experts gained both through theoretical development and practical implementation of intelligent systems in a variety of diverse application domains. This contributed volume offers a detailed and coherent picture of state-of-the-art,

This workshop will address the impact of robot morphology on HRI from the perspective of Interaction Science, which encompasses theory and design of human interaction with technology. Anthropomorphic designs, which are common, have to be balanced with the "uncanny valley effect," since different morphologies suggest different affordances to users, triggering a variety of cognitive heuristics and thereby shaping their interactions with robots. We expect progress towards more human-acceptable interactions with robots by understanding the cognitive, behavioral, organizational, and contextual factors of morphology in HRI, as well as new meta-theories and design guidelines. We emphasize a highly multi-disciplinary approach, by involving participants from social sciences, engineering, and design. Topics of presentation include but not limited to: Engineering considerations in designing robot morphology Empirical psychological considerations in designing robot morphology Aesthetic parameters for transcending the uncanny valley effect (UVE) with static, dynamic and interactive robots Physiological (fMRI) bases of UVE Cognitive heuristics triggered by morphological cues on robot interfaces Adaptation for multimodal robot interfaces Cognitive Robotic Engine for Dependable HRI Acceptance of Socially Interactive Robots Evaluation frameworks for human-like robots Robot appearances for social interactions among Autistic children

Page 1. Brain Mechanisms for Robotic Object Pose Estimation Eris Chinellato, Beata J. Grzyb and Angel P. del Pobil Abstract—Integration of multiple visual cues provides nat-ural systems with superior abilities in dealing with nearby objects. ...

Within the framework of a model of vision-based robotic grasping inspired on neuroscience data, we deal with the problem of object orientation estimation by analyzing human psychophysical data in order to reproduce them in an artificial setup. A set of ANN is ...

Do individual differences in dispositional behavioral tendencies, such as immersive tendency and need to belong, play a significant role in human-robot interaction? To answer this question, the present study conducted a 2 x 2 between-subjects experiment to examine the effects of immersive tendency (high vs. low) and need to belong (high vs. low) on individuals' perceptions of a social robot. Preliminary data analyses revealed that participants with a higher level of immersive tendency and need to belong showed greater attachment and trust towards the robot, and were more satisfied with their relationship with the robot than participants with a lower level of immersive tendency and need to belong. In addition, participants with a higher level of immersive tendency experienced greater feelings of social presence. Implications of notable findings are discussed.

Page 1. An Attempt Towards a General Representation Paradigm for Spatial Reasoning Angel P. del Pobil Computer Science Dept. Jaume I University Campus Penyeta Roja E-1207 1 CastelM, Spain E-mail: pobil@inf.uji.es MariaTeresaEscrig Jose Albert0 J&n ...