Ethological Modeling and Architecture for an Entertainment Robot

This paper presents a novel method for creating high-fidelity models of animal behavior for use in robotic systems based on a behavioral systems approach, and describes in particular how an ethological model of a domestic dog can be implemented with AIBO, the Sony entertainment robot

Adaptive Circadian Rhythms for Autonomous and Biologically Inspired Robot Behavior

Biological rhythms are periodic internal variations of living organisms that act as adaptive responses to environmental changes. The human pacemaker is the suprachiasmatic nucleus, a brain region involved in biological functions like homeostasis or emotion. Biological rhythms are ultradian (less than 24 h), circadian (~24 h), or infradian (>24 h) depending on their period. Circadian rhythms are the most studied since they regulate daily sleep, emotion, and activity. Ambient and internal stimuli, such as light or activity, influence the timing and the period of biological rhythms, making our bodies adapt to dynamic situations. Nowadays, robots experience unceasing development, assisting us in many tasks. Due to the dynamic conditions of social environments and human-robot interaction, robots exhibiting adaptive behavior have more possibilities to engage users by emulating human social skills. This paper presents a biologically inspired model based on circadian biorhythms for autonomous and adaptive robot behavior. The model uses the Dynamic Circadian Integrated Response Characteristic method to mimic human biology and control artificial biologically inspired functions influencing the robot's decision-making. The robot's clock adapts to light, ambient noise, and user activity, synchronizing the robot's behavior to the ambient conditions. The results show the adaptive response of the model to time shifts and seasonal changes of different ambient stimuli while regulating simulated hormones that are key in sleep/activity timing, stress, and autonomic basal heartbeat control during the day

On the utilisation of social animals as a model for social robotics

Social robotics is becoming a driving field in building artificial agents. The possibility to construct agents that can engage in meaningful social interaction with humans presents new challenges for the engineers. In general social robotics has been inspired dominantly by human psychology and aimed for building human-like robots. Only a small subcategory of companion robots (also referred to as robotic pets) was build to mimic animals. In the opinion essay we argue that all social robots should be seen as companions and more conceptual emphasis should be put on the inter-specific interaction between humans and social robots. This view is underlined by the means of an ethological analysis, and critical evaluation of present day companion robots. We suggest that human-animal interaction provides a rich source of knowledge for designing social robots that are able to interact with humans under a wide range of conditions

What could assistance robots learn from assistance dogs?

These studies are part of our broader project that aims at revealing relevant aspects of human-dog interactions, which could help to develop and test robot social behaviour. We suggest that the cooperation between assistance dogs and their disabled owners could serve as a model to design successful assistance robot–human interactions. In Study 1, we analysed the behaviour of 32 assistance dog–owner dyads performing a fetch and carry task. In addition to important typical behaviours (attracting attention, eye-contact, comprehending pointing gestures), we found differences depending on how experienced the dyad was and whether the owner used a wheel chair or not. In Study 2 we investigated the reactions of a subsample of dogs to unforeseen difficulties during a retrieving task. We revealed different types of communicative and displacement behaviours, and importantly, dogs showed a strong commitment to execute the insoluble task or at least their behaviours lent a “busy” appearance to them, which can attenuate the owners’ disappointment. We suggest that assistant robots should communicate their inability to solve a problem using simple behaviours (non-verbal vocalisation, orientation alternation), and/or could show displacement behaviours rather than simply not performing the task. In sum, we propose that assistant dogs’ communicative behaviours and problem solving strategies could inspire the development of the relevant functions and social behaviours of assistance robots

Towards self-explaining social robots. Verbal explanation strategies for a needs-based architecture

Stange S, Buschmeier H, Hassan T, Ritter C, Kopp S. Towards self-explaining social robots. Verbal explanation strategies for a needs-based architecture. Presented at the AAMAS 2019 Workshop on Cognitive Architectures for HRI: Embodied Models of Situated Natural Language Interactions (MM-Cog), Montréal, Canada.In order to establish long-term relationships with users, social companion robots and their behaviors need to be comprehensible. Purely reactive behavior such as answering questions or following commands can be readily interpreted by users. However, the robot's proactive behaviors, included in order to increase liveliness and improve the user experience, often raise a need for explanation. In this paper, we provide a concept to produce accessible “why-explanations” for the goal-directed behavior an autonomous, lively robot might produce. To this end we present an architecture that provides reasons for behaviors in terms of comprehensible needs and strategies of the robot, and we propose a model for generating different kinds of explanations

Social behaviours in dog-owner interactions can serve as a model of companion robot behaviour

It is essential for social robots to fit in the human society. In order to facilitate this process we propose to use the family dog’s social behaviour shown towards humans as an inspiration. In this study we explored dogs’ low level social monitoring in dog-human interactions and extracted individually consistent and context dependent behaviours in simple everyday social scenarios. We found that proximity seeking and tail wagging were most individually distinctive in dogs, while activity, orientation towards the owner, and exploration were dependent on the context and/or the activity of the owner. The functional analogues of these dog behaviours can be implemented in social robots of different embodiments in order to make them acceptable and more believable for humans

Going Beyond the "Synthetic Method": New Paradigms Cross-Fertilizing Robotics and Cognitive Neuroscience

In so-called ethorobotics and robot-supported social cognitive neurosciences, robots are used as scientific tools to study animal behavior and cognition. Building on previous epistemological analyses of biorobotics, in this article it is argued that these two research fields, widely differing from one another in the kinds of robots involved and in the research questions addressed, share a common methodology, which significantly differs from the "synthetic method" that, until recently, dominated biorobotics. The methodological novelty of this strategy, the research opportunities that it opens, and the theoretical and technological challenges that it gives rise to, will be discussed with reference to the peculiarities of the two research fields. Some broad methodological issues related to the generalization of results concerning robot-animal interaction to theoretical conclusions on animal-animal interaction will be identified and discussed

A biologically inspired architecture for an autonomous and social robot

Lately, lots of effort has been put into the construction of robots able to live among humans. This fact has favored the development of personal or social robots, which are expected to behave in a natural way. This implies that these robots could meet certain requirements, for example, to be able to decide their own actions (autonomy), to be able to make deliberative plans (reasoning), or to be able to have an emotional behavior in order to facilitate human-robot interaction. In this paper, the authors present a bioinspired control architecture for an autonomous and social robot, which tries to accomplish some of these features. In order to develop this new architecture, authors have used as a base a prior hybrid control architecture (AD) that is also biologically inspired. Nevertheless, in the later, the task to be accomplished at each moment is determined by a fix sequence processed by the Main Sequencer. Therefore, the main sequencer of the architecture coordinates the previously programmed sequence of skills that must be executed. In the new architecture, the main sequencer is substituted by a decision making system based on drives, motivations, emotions, and self-learning, which decides the proper action at every moment according to robot's state. Consequently, the robot improves its autonomy since the added decision making system will determine the goal and consequently the skills to be executed. A basic version of this new architecture has been implemented on a real robotic platform. Some experiments are shown at the end of the paper.This work has been supported by the Spanish Government through the project called “Peer to Peer Robot-Human Interaction” (R2H), of MEC (Ministry of Science and Education), the project “A new approach to social robotics” (AROS), of MICINN (Ministry of Science and Innovation), the CAM Project S2009/DPI-1559/ROBOCITY2030 II, developed by the research team RoboticsLab at the University Carlos III of Madrid