Unai Zabala - Academia.edu (original) (raw)
Papers by Unai Zabala
2021 IEEE International Conference on Robotics and Automation (ICRA), 2021
Talking gestures are a fundamental part of body language and, therefore, are also important for s... more Talking gestures are a fundamental part of body language and, therefore, are also important for social robots. Gesture generation by generative approaches is supposed to produce a more appropriate behavior than rule-based approaches. Usually, the evaluation of generated gestures is carried out by subjective visual evaluation, which could be cultural dependent and influenced by external factors. In this work we extend previous research on quantitative evaluation methods, comparing two generative methods and showing that their results correlate with subjective evaluation by a sizable group of people. The final goal is to offer a quantitative tool to help the researchers to automate the evaluation of their gesture generation systems, as a complementary measure to subjective methods.
Multimedia Tools and Applications, 2021
Natural gestures are a desirable feature for a humanoid robot, as they are presumed to elicit a m... more Natural gestures are a desirable feature for a humanoid robot, as they are presumed to elicit a more comfortable interaction in people. With this aim in mind, we present in this paper a system to develop a natural talking gesture generation behavior. A Generative Adversarial Network (GAN) produces novel beat gestures from the data captured from recordings of human talking. The data is obtained without the need for any kind of wearable, as a motion capture system properly estimates the position of the limbs/joints involved in human expressive talking behavior. After testing in a Pepper robot, it is shown that the system is able to generate natural gestures during large talking periods without becoming repetitive. This approach is computationally more demanding than previous work, therefore a comparison is made in order to evaluate the improvements. This comparison is made by calculating some common measures about the end effectors’ trajectories (jerk and path lengths) and complemente...
Advances in Intelligent Systems and Computing, 2020
Applied Sciences, 2021
Social robots must master the nuances of human communication as a mean to convey an effective mes... more Social robots must master the nuances of human communication as a mean to convey an effective message and generate trust. It is well-known that non-verbal cues are very important in human interactions, and therefore a social robot should produce a body language coherent with its discourse. In this work, we report on a system that endows a humanoid robot with the ability to adapt its body language according to the sentiment of its speech. A combination of talking beat gestures with emotional cues such as eye lightings, body posture of voice intonation and volume permits a rich variety of behaviors. The developed approach is not purely reactive, and it easily allows to assign a kind of personality to the robot. We present several videos with the robot in two different scenarios, and showing discrete and histrionic personalities.
Sensors, 2020
GidaBot is an application designed to setup and run a heterogeneous team of robots to act as tour... more GidaBot is an application designed to setup and run a heterogeneous team of robots to act as tour guides in multi-floor buildings. Although the tours can go through several floors, the robots can only service a single floor, and thus, a guiding task may require collaboration among several robots. The designed system makes use of a robust inter-robot communication strategy to share goals and paths during the guiding tasks. Such tours work as personal services carried out by one or more robots. In this paper, a face re-identification/verification module based on state-of-the-art techniques is developed, evaluated offline, and integrated into GidaBot’s real daily activities, to avoid new visitors interfering with those attended. It is a complex problem because, as users are casual visitors, no long-term information is stored, and consequently, faces are unknown in the training step. Initially, re-identification and verification are evaluated offline considering different face detectors...
Autonomous Robots, 2021
Social robot capabilities, such as talking gestures, are best produced using data driven approach... more Social robot capabilities, such as talking gestures, are best produced using data driven approaches to avoid being repetitive and to show trustworthiness. However, there is a lack of robust quantitative methods that allow to compare such methods beyond visual evaluation. In this paper a quantitative analysis is performed that compares two Generative Adversarial Networks based gesture generation approaches. The aim is to measure characteristics such as fidelity to the original training data, but at the same time keep track of the degree of originality of the produced gestures. Principal Coordinate Analysis and procrustes statistics are performed and a new Fréchet Gesture Distance is proposed by adapting the Fréchet Inception Distance to gestures. These three techniques are taken together to asses the fidelity/originality of the generated gestures.
2021 IEEE International Conference on Robotics and Automation (ICRA), 2021
Talking gestures are a fundamental part of body language and, therefore, are also important for s... more Talking gestures are a fundamental part of body language and, therefore, are also important for social robots. Gesture generation by generative approaches is supposed to produce a more appropriate behavior than rule-based approaches. Usually, the evaluation of generated gestures is carried out by subjective visual evaluation, which could be cultural dependent and influenced by external factors. In this work we extend previous research on quantitative evaluation methods, comparing two generative methods and showing that their results correlate with subjective evaluation by a sizable group of people. The final goal is to offer a quantitative tool to help the researchers to automate the evaluation of their gesture generation systems, as a complementary measure to subjective methods.
Multimedia Tools and Applications, 2021
Natural gestures are a desirable feature for a humanoid robot, as they are presumed to elicit a m... more Natural gestures are a desirable feature for a humanoid robot, as they are presumed to elicit a more comfortable interaction in people. With this aim in mind, we present in this paper a system to develop a natural talking gesture generation behavior. A Generative Adversarial Network (GAN) produces novel beat gestures from the data captured from recordings of human talking. The data is obtained without the need for any kind of wearable, as a motion capture system properly estimates the position of the limbs/joints involved in human expressive talking behavior. After testing in a Pepper robot, it is shown that the system is able to generate natural gestures during large talking periods without becoming repetitive. This approach is computationally more demanding than previous work, therefore a comparison is made in order to evaluate the improvements. This comparison is made by calculating some common measures about the end effectors’ trajectories (jerk and path lengths) and complemente...
Advances in Intelligent Systems and Computing, 2020
Applied Sciences, 2021
Social robots must master the nuances of human communication as a mean to convey an effective mes... more Social robots must master the nuances of human communication as a mean to convey an effective message and generate trust. It is well-known that non-verbal cues are very important in human interactions, and therefore a social robot should produce a body language coherent with its discourse. In this work, we report on a system that endows a humanoid robot with the ability to adapt its body language according to the sentiment of its speech. A combination of talking beat gestures with emotional cues such as eye lightings, body posture of voice intonation and volume permits a rich variety of behaviors. The developed approach is not purely reactive, and it easily allows to assign a kind of personality to the robot. We present several videos with the robot in two different scenarios, and showing discrete and histrionic personalities.
Sensors, 2020
GidaBot is an application designed to setup and run a heterogeneous team of robots to act as tour... more GidaBot is an application designed to setup and run a heterogeneous team of robots to act as tour guides in multi-floor buildings. Although the tours can go through several floors, the robots can only service a single floor, and thus, a guiding task may require collaboration among several robots. The designed system makes use of a robust inter-robot communication strategy to share goals and paths during the guiding tasks. Such tours work as personal services carried out by one or more robots. In this paper, a face re-identification/verification module based on state-of-the-art techniques is developed, evaluated offline, and integrated into GidaBot’s real daily activities, to avoid new visitors interfering with those attended. It is a complex problem because, as users are casual visitors, no long-term information is stored, and consequently, faces are unknown in the training step. Initially, re-identification and verification are evaluated offline considering different face detectors...
Autonomous Robots, 2021
Social robot capabilities, such as talking gestures, are best produced using data driven approach... more Social robot capabilities, such as talking gestures, are best produced using data driven approaches to avoid being repetitive and to show trustworthiness. However, there is a lack of robust quantitative methods that allow to compare such methods beyond visual evaluation. In this paper a quantitative analysis is performed that compares two Generative Adversarial Networks based gesture generation approaches. The aim is to measure characteristics such as fidelity to the original training data, but at the same time keep track of the degree of originality of the produced gestures. Principal Coordinate Analysis and procrustes statistics are performed and a new Fréchet Gesture Distance is proposed by adapting the Fréchet Inception Distance to gestures. These three techniques are taken together to asses the fidelity/originality of the generated gestures.