A biologically inspired decision-making system for the autonomous adaptive behavior of social robots

The decisions made by social robots while they fulfill their tasks have a strong influence on their performance. In these contexts, autonomous social robots must exhibit adaptive and social-based behavior to make appropriate decisions and operate correctly in complex and dynamic scenarios. This paper presents a Decision-Making System for social robots working on long-term interactions like cognitive stimulation or entertainment. The Decision-making System employs the robot's sensors, user information, and a biologically inspired module to replicate how human behavior emerges in the robot. Besides, the system personalizes the interaction to maintain the users' engagement while adapting to their features and preferences, overcoming possible interaction limitations. The system evaluation was in terms of usability, performance metrics, and user perceptions. We used the Mini social robot as the device where we integrated the architecture and carried out the experimentation. The usability evaluation consisted of 30 participants interacting with the autonomous robot in 30 min sessions. Then, 19 participants evaluated their perceptions of robot attributes of the Godspeed questionnaire by playing with the robot in 30 min sessions. The participants rated the Decision-making System with excellent usability (81.08 out of 100 points), perceiving the robot as intelligent (4.28 out of 5), animated (4.07 out of 5), and likable (4.16 out of 5). However, they also rated Mini as unsafe (security perceived as 3.15 out of 5), probably because users could not influence the robot's decisions.

SoftSAR: The New Softer Side of Socially Assistive Robots-Soft Robotics with Social Human-Robot Interaction Skills

When we think of "soft" in terms of socially assistive robots (SARs), it is mainly in reference to the soft outer shells of these robots, ranging from robotic teddy bears to furry robot pets. However, soft robotics is a promising field that has not yet been leveraged by SAR design. Soft robotics is the incorporation of smart materials to achieve biomimetic motions, active deformations, and responsive sensing. By utilizing these distinctive characteristics, a new type of SAR can be developed that has the potential to be safer to interact with, more flexible, and uniquely uses novel interaction modes (colors/shapes) to engage in a heighted human-robot interaction. In this perspective article, we coin this new collaborative research area as SoftSAR. We provide extensive discussions on just how soft robotics can be utilized to positively impact SARs, from their actuation mechanisms to the sensory designs, and how valuable they will be in informing future SAR design and applications. With extensive discussions on the fundamental mechanisms of soft robotic technologies, we outline a number of key SAR research areas that can benefit from using unique soft robotic mechanisms, which will result in the creation of the new field of SoftSAR.

Gaze Control of a Robotic Head for Realistic Interaction With Humans

When there is an interaction between a robot and a person, gaze control is very important for face-to-face communication. However, when a robot interacts with several people, neurorobotics plays an important role to determine the person to look at and those to pay attention to among the others. There are several factors which can influence the decision: who is speaking, who he/she is speaking to, where people are looking, if the user wants to attract attention, etc. This article presents a novel method to decide who to pay attention to when a robot interacts with several people. The proposed method is based on a competitive network that receives different stimuli (look, speak, pose, hoard conversation, habituation, etc.) that compete with each other to decide who to pay attention to. The dynamic nature of this neural network allows a smooth transition in the focus of attention to a significant change in stimuli. A conversation is created between different participants, replicating human behavior in the robot. The method deals with the problem of several interlocutors appearing and disappearing from the visual field of the robot. A robotic head has been designed and built and a virtual agent projected on the robot's face display has been integrated with the gaze control. Different experiments have been carried out with that robotic head integrated into a ROS architecture model. The work presents the analysis of the method, how the system has been integrated with the robotic head and the experiments and results obtained.

“Hmm, Did You Hear What I Just Said?”: Development of a Re-Engagement System for Socially Interactive Robots

Maintaining engagement is challenging in human–human interaction. When disengagements happen, people try to adapt their behavior with an expectation that engagement will be regained. In human–robot interaction, although socially interactive robots are engaging, people can easily drop engagement while interacting with robots. This paper proposes a multi-layer re-engagement system that applies different strategies through human-like verbal and non-verbal behaviors to regain user engagement, taking into account the user’s attention level and affective states. We conducted a usability test in a robot storytelling scenario to demonstrate technical operation of the system as well as to investigate how people react when interacting with a robot with re-engagement ability. Our usability test results reveal that the system has the potential to maintain a user’s engagement. Our selected users gave positive comments, through open-ended questions, to the robot with this ability. They also rated the robot with the re-engagement ability higher on several dimensions, i.e., animacy, likability, and perceived intelligence.

Anthropomorphic Design: Emotional Perception for Deformable Object

Despite the increasing number of studies on user experience (UX) and user interfaces (UI), few studies have examined emotional interaction between humans and deformable objects. In the current study, we investigated how the anthropomorphic design of a flexible display interacts with emotion. For 101 unique 3D images in which an object was bent at different axes, 281 participants were asked to report how strongly the object evoked five elemental emotions (e.g., happiness, disgust, anger, fear, and sadness) in an online survey. People rated the object’s shape using three emotional categories: happiness, disgust–anger, and sadness–fear. It was also found that a combination of axis of bending (horizontal or diagonal axis) and convexity (bending convexly or concavely) predicted emotional valence, underpinning the anthropomorphic design of flexible displays. Our findings provide empirical evidence that axis of bending and convexity can be an important antecedent of emotional interaction with flexible objects, triggering at least three types of emotion in users.

A Survey on Behavior Control Architectures for Social Robots in Healthcare Interventions

The use of Robot-Assisted Therapy (RAT) in healthcare interventions has increasingly received research attention. However, a lot of RAT studies are conducted under Wizard of Oz (WoZ) techniques in which the robots are teleoperated or pre-programmed. The trend of RAT is moving towards (partially) autonomous control in which the robot behavior control architecture plays a significant role in creating effective human–robot interaction by engaging and motivating human users into the therapeutic processes. This paper describes the state-of-the-art of the autonomous behavior control architectures currently developed for social robots in healthcare interventions, considering both clinical and exploratory studies. We also present certain requirements that an architecture used in RAT study should acquire, which provide roboticists and therapists an inspiration to orient their designs and implementations on the basis of their targeted RAT applications.