Figure 3 - uploaded by Javier Ruiz-del-Solar
Content may be subject to copyright.
Software architecture. (Top) Low-level control processes running on dedicated hardware. All high-level processes run on the tablet PC or on the notebooks. (Bottom) The hardware components: chest, head, arm and hand, and platform.
Source publication
The main goal of this article is to describe Bender, a general-purpose social robot with human–robot interaction capabilities, and to report and analyze its applicability in three different natural environments: (i) home settings, (ii) school classrooms, and (iii) public places. Evaluation of the robot’s performance is based on its ability to detec...
Context in source publication
Context 1
... main components of our software architecture are shown in Figure 3. Speech synthesis and analysis, as well as vision tasks (general object recognition; face, hand, and gesture recognition), are performed on the Windows 7-based Dell Alienware notebook, whereas the Navigation and Mapping modules are run from the other Dell Alienware notebook (running Linux). ...
Similar publications
Over decades, social robotics has evolved as a concept that presently covers different areas of application, and interacts with different domains in technology, education, medicine and others. Today, it is possible to envision social robots in tasks that were not expected years ago, and that is not only due to the evolution of social robots, but al...
In this paper we discuss the role of context information in the interaction process between social robots and people with special characteristics, which we claim to be a key factor to improve interactive features in robots and systems. We address the difference between situation and context, present its current use in nowadays applications and the...
Improving the quality of life of people with dementia in long-term care facilities is very important and can be achieved by designing engaging activities for the residents. The introduction of social robots for people with dementia has already proven its benefits, and we expected that adding contextual cues to this interaction would enhance the pos...
This mini review discusses the use of social robots in a translanguaging pedagogy: the use of robots to enable students to use their full linguistic repertoire within schools, so any language that they speak at home or in another aspect of their lives. Current research on robot-assisted second-language learning is reviewed with the aim of finding o...
The use of robots in child education has emerged as a promising social human-robot interaction domain. Our experiment considering the effect of robotic embodiment on child learning reveals significant overall learning effects, but no significant differences between conditions. However, the real robot attracts significantly more gaze from the child...
Citations
... The robot uses three computers: a tablet for providing an user interface, and two Alienware computers, one dedicated to computer vision and the other dedicated to planning and navigation. The electronic and mechanical hardware components of the robot, as well as its software architecture, are described in [28]. The "person-following" behavior has been tested in indoor and outdoor daily life environments, such as the ones shown in Fig. 7. ...
In many robotic applications there is the need for detecting and tracking moving and/or static objects while the robot moves, in order to interact with them. High quality detection methods require considerable computational time when the number of objects to be detected is high, or when operating within dynamic, real-world environments. Then, when an object detection result is available, it is referred to a previous frame and not to the current one. A method for obtaining delay-free detections is introduced in this present article. It consists of projecting a delayed detection onto the current frame by using a set of feature tracks generated by using the KLT (Kanade-Lucas-Tomasi) tracker. The proposed method is shown to improve detection accuracy when the tracked object is moving with respect to the camera. In addition, the method is able to detect and manage false detections and occlusions using statistical classifiers (Support Vector Machine) and the Viterbi algorithm (Viterbi, IEEE Trans. Inf. Theory 13(2), 260–269 1967). The method is validated in a person-following task, and compared against a part-based HOG person detector, and four performant tracking methods (Meanshift, Compressive Tracking, Tracking-by-detection with Kernels and Kernelized Correlation Filter). Additionally, the method is validated in two additional tasks: face tracking and car tracking. In all reported experiments, the proposed method obtains the best performance among all compared methods.
... The expression of emotion allows robots to communicate emotional states during the execution of a task like Lisa 8 and Bender. 15 In social interaction, facial expressions help to communicate an emotional and mental state which is expected to be consistent. A common problem is how to access people's mental state 16 as this cannot be perceived directly and must be inferred to by observers. ...
The facial expression of angry emotion can be useful to direct the interaction between agents, especially in unclear and cluttered environments. During the presence of an angry face, a process of analysis and diagnosis is activated in the subject that notices it, which could impact its behavior toward the one who expresses the emotion. In order to study such an effect in human–robot interaction, an expressive robotics face was designed and constructed. The influence of this face on human action and attention was analyzed in two collaborative tasks. Results of a digital survey, experimental interaction, and a questionnaire indicated that anger is the best recognized universal facial expression, has a regulatory effect in human action, and induces human attention when an unclear condition arises during the task. An additional finding was that the prolonged presence of an angry face reduces its impact compared to positive expressions.
... The expression of emotions has been used in service robots to enhance human-robot interaction (e.g., Lisa Robot [28] and Bender Robot [29]). This is of interest since the effect of emotional behavior during human-robot collaboration helps to enhance activities in daily life environments. ...
In this paper a strategy for incorporating a flexible and reliable high-level inference module in service robots is presented. This module is a part of the robot's cognitive architecture which coordinates perception, inference and action within the robot's communication and interaction cycle. The present approach relies on an explicit representation of the structure of the task performed by the robot. There are three kinds of inferences that the robot can use opportunistically along the task: (1) diagnosis, (2) decision making and (3) planning; each kind can be used in specific situations of the task structure or performed in arbitrary situations with recovery purposes when there is an interaction failure. In this latter case the three kinds of inference are performed sequentially in what we call the daily-life inference cycle. The inference cycle allows the incorporation of basic emotions in the robot's behavior. A case study incorporating these functionalities in the robot Golem-III is presented. The paper is concluded with a reflection on the opportunistic use of inference schemes to support flexible and robust behavior, including the expression of emotions, in service robots.
... Real world experiments using a service robot (Bender [32,33]; see Fig. 7) and a domestic home-like environment were carried out. The robot, which has participated in several service robotics competitions (e.g. ...
The main goal of this paper is to propose a Bayesian based methodology for implementing robot informed search for objects. The methodology uses convolutions between observation likelihoods of secondary objects and spatial relation masks for estimating the probability map of the object being searched for, and also a search procedure that uses this probability map. A method for computing complex spatial relation masks by using a basis composed of basic relation masks and a database of co-occurrences of objects is used. Each basic relation mask corresponds to a qualitative spatial relation (QSR), such as: ‘very near’, ‘near’, or ‘far’. The search procedure takes into account the probability that the main object can be in different regions on the map and the distance to those regions. Also, the object search procedure is able to detect objects and generate new plans while moving. The proposed methodology is compared with uninformed and alternative informed search approaches using simulations and real-world experiments with a service robot. In simulations, the use of the proposed methodology increases the detection rate from 28% (direct uninformed search) to 79%, when the main object can be detected within a maximum distance of 1 meter. In the real world experiments, the use of the proposed methodology increases the detection rate from 40% (direct uninformed search) to 87% when using convolutions with soft masks, global search, and information on the positive detection of secondary objects. The detection rates obtained when using the proposed methodology are also much higher than those obtained by alternative informed search methods, both in the simulated and in the real-world experiments.
... A service robot, Bender [56], was used as the platform for testing the different object recognition approaches. The robot has a Kinect camera and an RGB camera mounted over its head. ...
The main goal of this survey is to present a complete analysis of object recognition methods based on local invariant features from a robotics perspective; a summary which can be used by developers of robot vision applications in the selection and development of object recognition systems. The survey includes a brief description of the main approaches reported in the literature, with more specific analyses of local interest point computation methods, local descriptor computation and matching methods, and geometric verification methods. Different methods are analyzed by considering the main requirements of robotics applications, such as real-time operation with limited on-board computational resources, and constrained observational conditions derived from the robot geometry (e.g. limited camera resolution). In addition, various object recognition systems are evaluated in a service-robot domestic environment, where the final task to be performed by a service robot is the manipulation of objects. It can be concluded from the results reported that (i) the most suitable keypoint detectors are ORB, BRISK, Fast Hessian, and DoG, (ii) the most suitable descriptors are ORB, BRISK, SIFT, and SURF, (iii) the final performance of object recognition systems using local invariant features under real-world conditions depends strongly on the geometric verification methods being used, and (iv) the best performing object recognition systems are built using ORB-ORB and DoG-SIFT keypoint-descriptor combinations. ORB-ORB based systems are faster, while DoG-SIFT are more robust to real-world conditions.
... In [27], the ability of the robot to interact freely with humans using only speech and visual cues in a public space setting is evaluated. Experiments were carried out with 83 university students, and the main results were: 1) students could recognize the robot's facial expression in 70.6% of the cases; 2) 83.9% of them evaluated the robot's appearance as excellent or good; 3) 88.5% evaluated the robot's ability to express emotions as excellent or good; 4) 80.7% evaluated the robot's ability to interact with humans as excellent or good; 5) 90% thought that it was easy to interact with the robot; 6) 84% believed that the robot is suitable to be used as a receptionist, museum guide, or butler; and 7) 67% thought that the robot could be used for educational purposes with children. ...
Nowadays, universities are making extensive efforts to attract prospective students to the fields of electrical, electronic, and computer engineering. Thus, outreach is becoming increasingly important, and activities with schoolchildren are being extensively carried out as part of this effort. In this context, robotics is a very attractive and effective tool for fostering interest in science and technology among children and young people and for attracting them toward engineering. In this article, experience with different robotics-centered outreach activities in the Universidad de Chile (UCH), Santiago, Chile, will be shared. These activities include robotics courses for children, social robots as keynote speakers, mechatronics design courses, and participation in international robotics competitions, which contribute synergistically to the goal of attracting students to UCH's Electrical Engineering (EE) Department. Owing to its novelty, the use of social robots as keynote speakers for schoolchildren will be described in detail. Experimental results that demonstrate how sophisticated social robots can be used to foster the interest of young people in technology will be shown. Altogether, more than 3000 schoolchildren have participated directly in these outreach activities here in Chile, creating a sizeable impact in this country.
In this chapter, we discuss algorithmic writing futures with specific focus on analytics and artificial intelligence (see Table 3.1). We examine the impact on writing futures in terms of algorithmic control and algorithmic culture and how our teaching, writing, cognition, and behavior is being steered by learning management systems. We emphasize the need for transparency for proprietary “black box” decision-making systems and that the TPC community will often be on the frontline tasked with recognizing, reporting, and/or ameliorating bias in teams with developers, AI nonhuman agents, and an array of public or private entities that are starting to classify these types of issues. This will form another analytical skill in the collaborative relationship between writers, adjacent professionals, and AI actors. We conclude with detail on how AI might assist in recognizing, ameliorating, and addressing civic challenges. Here we include content about several relevant international endeavors to establish principles, practices, and standards for ethical AI, many of which reference communication practices.
