100 research outputs found
Enhancing the Sense of Attention from an Assistance Mobile Robot by Improving Eye-Gaze Contact from Its Iconic Face Displayed on a Flat Screen
One direct way to express the sense of attention in a human interaction is through the
gaze. This paper presents the enhancement of the sense of attention from the face of a human-sized
mobile robot during an interaction. This mobile robot was designed as an assistance mobile robot
and uses a flat screen at the top of the robot to display an iconic (simplified) face with big round
eyes and a single line as a mouth. The implementation of eye-gaze contact from this iconic face is a
problem because of the difficulty of simulating real 3D spherical eyes in a 2D image considering the
perspective of the person interacting with the mobile robot. The perception of eye-gaze contact has
been improved by manually calibrating the gaze of the robot relative to the location of the face of the
person interacting with the robot. The sense of attention has been further enhanced by implementing
cyclic face explorations with saccades in the gaze and by performing blinking and small movements
of the mouth
Systematic Odometry Error Evaluation and Correction in a Human-Sized Three-Wheeled Omnidirectional Mobile Robot Using Flower-Shaped Calibration Trajectories
Odometry is a simple and practical method that provides a periodic real-time estimation of
the relative displacement of a mobile robot based on the measurement of the angular rotational speed
of its wheels. The main disadvantage of odometry is its unbounded accumulation of errors, a factor
that reduces the accuracy of the estimation of the absolute position and orientation of a mobile robot.
This paper proposes a general procedure to evaluate and correct the systematic odometry errors of a
human-sized three-wheeled omnidirectional mobile robot designed as a versatile personal assistant
tool. The correction procedure is based on the definition of 36 individual calibration trajectories
which together depict a flower-shaped figure, on the measurement of the odometry and ground
truth trajectory of each calibration trajectory, and on the application of several strategies to iteratively
adjust the effective value of the kinematic parameters of the mobile robot in order to match the
estimated final position from these two trajectories. The results have shown an average improvement
of 82.14% in the estimation of the final position and orientation of the mobile robot. Therefore, these
results can be used for odometry calibration during the manufacturing of human-sized three-wheeled
omnidirectional mobile robots
The Assistant Personal Robot Project: From the APR-01 to the APR-02 Mobile Robot Prototypes
This paper describes the evolution of the Assistant Personal Robot (APR) project developed at the Robotics Laboratory of the University of Lleida, Spain. This paper describes the first APR-01 prototype developed, the basic hardware improvement, the specific anthropomorphic improvements, and the preference surveys conducted with engineering students from the same university in order to maximize the perceived affinity with the final APR-02 mobile robot prototype. The anthropomorphic improvements have covered the design of the arms, the implementation of the arm and symbolic hand, the selection of a face for the mobile robot, the selection of a neutral facial expression, the selection of an animation for the mouth, the application of proximity feedback, the application of gaze feedback, the use of arm gestures, the selection of the motion planning strategy, and the selection of the nominal translational velocity. The final conclusion is that the development of preference surveys during the implementation of the APR-02 prototype has greatly influenced its evolution and has contributed to increase the perceived affinity and social acceptability of the prototype, which is now ready to develop assistance applications in dynamic workspaces.This research was partially funded by the Accessibility Chair promoted by Indra, Adecco Foundation and the University of Lleida Foundation from 2006 to 2018. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results
Application of a Single-Type eNose to Discriminate the Brewed Aroma of One Caffeinated and Decaffeinated Encapsulated Espresso Coffee Type
This paper assesses a custom single-type electronic nose (eNose) applied to differentiate
the complex aromas generated by the caffeinated and decaffeinated versions of one encapsulated
espresso coffee mixture type. The eNose used is composed of 16 single-type (identical) metal–oxide
semiconductor (MOX) gas sensors based on microelectromechanical system (MEMS). This eNose
proposal takes advantage of the small but inherent sensing variability of MOX gas sensors in order to
provide a multisensorial description of volatiles or aromas. Results have shown that the information
provided with this eNose processed using LDA is able to successfully discriminate the complex
aromas of one caffeinated and decaffeinated encapsulated espresso coffee type
Classification of Three Volatiles Using a Single-Type eNose with Detailed Class-Map Visualization
The use of electronic noses (eNoses) as analysis tools are growing in popularity; however, the lack of a comprehensive, visual representation of how the different classes are organized and distributed largely complicates the interpretation of the classification results, thus reducing their practicality. The new contributions of this paper are the assessment of the multivariate classification performance of a custom, low-cost eNose composed of 16 single-type (identical) MOX gas sensors for the classification of three volatiles, along with a proposal to improve the visual interpretation of the classification results by means of generating a detailed 2D class-map representation based on the inverse of the orthogonal linear transformation obtained from a PCA and LDA analysis. The results showed that this single-type eNose implementation was able to perform multivariate classification, while the class-map visualization summarized the learned features and how these features may affect the performance of the classification, simplifying the interpretation and understanding of the eNose results
Assessing over Time Performance of an eNose Composed of 16 Single-Type MOX Gas Sensors Applied to Classify Two Volatiles
This paper assesses the over time performance of a custom electronic nose (eNose) composed of an array of commercial low-cost and single-type miniature metal-oxide (MOX) semiconductor gas sensors. The eNose uses 16 BME680 versatile sensor devices, each including an embedded
non-selective MOX gas sensor that was originally proposed to measure the total volatile organic
compounds (TVOC) in the air. This custom eNose has been used previously to detect ethanol and
acetone, obtaining initial promising classification results that worsened over time because of sensor
drift. The current paper assesses the over time performance of different classification methods applied
to process the information gathered from the eNose. The best classification results have been obtained
when applying a linear discriminant analysis (LDA) to the normalized conductance of the sensing
layer of the 16 MOX gas sensors available in the eNose. The LDA procedure by itself has reduced the
influence of drift in the classification performance of this single-type eNose during an evaluation
period of three month
Optimal droop control for voltage source converters in islanded microgrids
Postprint (published version
Evaluation of the Path-Tracking Accuracy of a Three-Wheeled Omnidirectional Mobile Robot Designed as a Personal Assistant
This paper presents the empirical evaluation of the path-tracking accuracy of a three-wheeled omnidirectional mobile robot that is able to move in any direction while simultaneously changing its orientation. The mobile robot assessed in this paper includes a precise onboard LIDAR for obstacle avoidance, self-location and map creation, path-planning and path-tracking. This mobile robot has been used to develop several assistive services, but the accuracy of its path-tracking system has not been specifically evaluated until now. To this end, this paper describes the kinematics and path-planning procedure implemented in the mobile robot and empirically evaluates the accuracy of its path-tracking system that corrects the trajectory. In this paper, the information gathered by the LIDAR is registered to obtain the ground truth trajectory of the mobile robot in order to estimate the path-tracking accuracy of each experiment conducted. Circular and eight-shaped trajectories were assessed with different translational velocities. In general, the accuracy obtained in circular trajectories is within a short range, but the accuracy obtained in eight-shaped trajectories worsens as the velocity increases. In the case of the mobile robot moving at its nominal translational velocity, 0.3 m/s, the root mean square (RMS) displacement error was 0.032 m for the circular trajectory and 0.039 m for the eight-shaped trajectory; the absolute maximum displacement errors were 0.077 m and 0.088 m, with RMS errors in the angular orientation of 6.27° and 7.76°, respectively. Moreover, the external visual perception generated by these error levels is that the trajectory of the mobile robot is smooth, with a constant velocity and without perceiving trajectory corrections
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