Behavioural comparison of human-animal (dog) and human-robot (AIBO) interactions

The behavioural analysis of human-robot interactions can help in developing socially interactive robots. The current study analyzes human-robot interaction with Theme software and the corresponding pattern detection algorithm. The method is based on the analysis of the temporal structure of the interactions by detecting T-patterns in the behaviour. We have compared humans' (children and adults) play behaviour interacting either with an AIBO or a living dog puppy. The analysis based on measuring latencies and frequencies of behavioural units suggested limited differences, e.g. the latency of humans touching the dog/AIBO was similar. In addition other differences could be accounted for by the limited abilities of the robot to interact with objects. Although the number of interactive T-patterns did not significantly differ among the groups but the partner's type (whether humans were playing with dog or AIBO) had a significant effect on the structure of the patterns. Both children and adults terminated T-patterns more frequently when playing with AIBO than when playing with the dog puppy, which suggest that the robot has a limited ability to engage in temporally structured behavioural interactions with humans. As other human studies suggest that the temporal complexity of the interaction is good measure of the partner's attitude, we suggest that more attention should be paid in the future to the robots' ability to engage in cooperative interaction with humans.     

A Bayesian Developmental Approach to Robotic Goal-Based Imitation Learning

A fundamental challenge in robotics today is building robots that can learn new skills by observing humans and imitating human actions. We propose a new Bayesian approach to robotic learning by imitation inspired by the developmental hypothesis that children use self-experience to bootstrap the process of intention recognition and goal-based imitation. Our approach allows an autonomous agent to: (i) learn probabilistic models of actions through self-discovery and experience, (ii) utilize these learned models for inferring the goals of human actions, and (iii) perform goal-based imitation for robotic learning and human-robot collaboration. Such an approach allows a robot to leverage its increasing repertoire of learned behaviors to interpret increasingly complex human actions and use the inferred goals for imitation, even when the robot has very different actuators from humans. We demonstrate our approach using two different scenarios: (i) a simulated robot that learns human-like gaze following behavior, and (ii) a robot that learns to imitate human actions in a tabletop organization task. In both cases, the agent learns a probabilistic model of its own actions, and uses this model for goal inference and goal-based imitation. We also show that the robotic agent can use its probabilistic model to seek human assistance when it recognizes that its inferred actions are too uncertain, risky, or impossible to perform, thereby opening the door to human-robot collaboration.     

Haptic/Graphic Rehabilitation: Integrating a Robot into a Virtual Environment Library and Applying it to Stroke Therapy

Recent research that tests interactive devices for prolonged therapy practice has revealed new prospects for robotics combined with graphical and other forms of biofeedback. Previous human-robot interactive systems have required different software commands to be implemented for each robot leading to unnecessary developmental overhead time each time a new system becomes available. For example, when a haptic/graphic virtual reality environment has been coded for one specific robot to provide haptic feedback, that specific robot would not be able to be traded for another robot without recoding the program. However, recent efforts in the open source community have proposed a wrapper class approach that can elicit nearly identical responses regardless of the robot used. The result can lead researchers across the globe to perform similar experiments using shared code. Therefore modular "switching out"of one robot for another would not affect development time. In this paper, we outline the successful creation and implementation of a wrapper class for one robot into the open-source H3DAPI, which integrates the software commands most commonly used by all robots.     

Emotion Attribution to a Non-Humanoid Robot in Different Social Situations

In the last few years there was an increasing interest in building companion robots that interact in a socially acceptable way with humans. In order to interact in a meaningful way a robot has to convey intentionality and emotions of some sort in order to increase believability. We suggest that human-robot interaction should be considered as a specific form of inter-specific interaction and that human–animal interaction can provide a useful biological model for designing social robots. Dogs can provide a promising biological model since during the domestication process dogs were able to adapt to the human environment and to participate in complex social interactions. In this observational study we propose to design emotionally expressive behaviour of robots using the behaviour of dogs as inspiration and to test these dog-inspired robots with humans in inter-specific context. In two experiments (wizard-of-oz scenarios) we examined humans'' ability to recognize two basic and a secondary emotion expressed by a robot. In Experiment 1 we provided our companion robot with two kinds of emotional behaviour (“happiness” and “fear”), and studied whether people attribute the appropriate emotion to the robot, and interact with it accordingly. In Experiment 2 we investigated whether participants tend to attribute guilty behaviour to a robot in a relevant context by examining whether relying on the robot''s greeting behaviour human participants can detect if the robot transgressed a predetermined rule. Results of Experiment 1 showed that people readily attribute emotions to a social robot and interact with it in accordance with the expressed emotional behaviour. Results of Experiment 2 showed that people are able to recognize if the robot transgressed on the basis of its greeting behaviour. In summary, our findings showed that dog-inspired behaviour is a suitable medium for making people attribute emotional states to a non-humanoid robot.     

Cooperation and the evolution of intelligence

The high levels of intelligence seen in humans, other primates, certain cetaceans and birds remain a major puzzle for evolutionary biologists, anthropologists and psychologists. It has long been held that social interactions provide the selection pressures necessary for the evolution of advanced cognitive abilities (the 'social intelligence hypothesis'), and in recent years decision-making in the context of cooperative social interactions has been conjectured to be of particular importance. Here we use an artificial neural network model to show that selection for efficient decision-making in cooperative dilemmas can give rise to selection pressures for greater cognitive abilities, and that intelligent strategies can themselves select for greater intelligence, leading to a Machiavellian arms race. Our results provide mechanistic support for the social intelligence hypothesis, highlight the potential importance of cooperative behaviour in the evolution of intelligence and may help us to explain the distribution of cooperation with intelligence across taxa.     

Interactive language learning by robots: the transition from babbling to word forms

The advent of humanoid robots has enabled a new approach to investigating the acquisition of language, and we report on the development of robots able to acquire rudimentary linguistic skills. Our work focuses on early stages analogous to some characteristics of a human child of about 6 to 14 months, the transition from babbling to first word forms. We investigate one mechanism among many that may contribute to this process, a key factor being the sensitivity of learners to the statistical distribution of linguistic elements. As well as being necessary for learning word meanings, the acquisition of anchor word forms facilitates the segmentation of an acoustic stream through other mechanisms. In our experiments some salient one-syllable word forms are learnt by a humanoid robot in real-time interactions with naive participants. Words emerge from random syllabic babble through a learning process based on a dialogue between the robot and the human participant, whose speech is perceived by the robot as a stream of phonemes. Numerous ways of representing the speech as syllabic segments are possible. Furthermore, the pronunciation of many words in spontaneous speech is variable. However, in line with research elsewhere, we observe that salient content words are more likely than function words to have consistent canonical representations; thus their relative frequency increases, as does their influence on the learner. Variable pronunciation may contribute to early word form acquisition. The importance of contingent interaction in real-time between teacher and learner is reflected by a reinforcement process, with variable success. The examination of individual cases may be more informative than group results. Nevertheless, word forms are usually produced by the robot after a few minutes of dialogue, employing a simple, real-time, frequency dependent mechanism. This work shows the potential of human-robot interaction systems in studies of the dynamics of early language acquisition.     

Role of expressive behaviour for robots that learn from people

Robotics has traditionally focused on developing intelligent machines that can manipulate and interact with objects. The promise of personal robots, however, challenges researchers to develop socially intelligent robots that can collaborate with people to do things. In the future, robots are envisioned to assist people with a wide range of activities such as domestic chores, helping elders to live independently longer, serving a therapeutic role to help children with autism, assisting people undergoing physical rehabilitation and much more. Many of these activities shall require robots to learn new tasks, skills and individual preferences while ‘on the job’ from people with little expertise in the underlying technology. This paper identifies four key challenges in developing social robots that can learn from natural interpersonal interaction. The author highlights the important role that expressive behaviour plays in this process, drawing on examples from the past 8 years of her research group, the Personal Robots Group at the MIT Media Lab.     

Parasitic Robot System for Waypoint Navigation of Turtle

In research on small mobile robots and biomimetic robots,locomotion ability remains a major issue despite many advances in technology.However,evolution has led to there being many real animals capable of excellent locomotion.This paper presents a "parasitic robot system" whereby locomotion abilities of an animal are applied to a robot task.We chose a turtle as our first host animal and designed a parasitic robot that can perform "operant conditioning".The parasitic robot,which is attached to the turtle,can induce object-tracking behavior of the turtle toward a Light Emitting Diode (LED) and positively reinforce the behavior through repeated stimulus-response interaction.After training sessions over five weeks,the robot could successfully control the direction of movement of the trained turtles in the waypoint navigation task.This hybrid animal-robot interaction system could provide an alternative solution to some of the limitations of conventional mobile robot systems in various fields,and could also act as a useful interaction system for the behavioral sciences.     

Study on Decentralization of Spherical Amphibious Multi-robot Control System Based on Smart Contract and Blockchain

With the development of intelligent bionic robots and the improvement of military application,a single robot cannot meet the requirements of the tasks of the current era.The more complex tasks require not only that the robot be able to pass through the field barriers and the amphibious environment,but also that the robot be able to collaborate in a multi-robot system.Consequently,research on the multi-robot control system of spherical amphibious robots is very important.Pres-ently,the main research on amphibious robots is to improve the functions of a single robot,in the absence of the study of the multi-robot control system.Existing systems primarily use a centralized control methodology.Although the transfer of central node can be achieved,there is still a problem of Byzantine fault tolerance in military applications,that is,when the amphibious multi-robot system is invaded by the enemy.The central node may not only fail to accomplish the task,but also lose control of other robots,with severe consequences.To solve the above problems,this paper proposed a decentralized method of spherical amphibious multi-robot control system based on blockchain technology.First,the point-to-point informa-tion network based on long range radio technology of low power wide area network was set up,we designed the blockchain system for embedded application environment and the decentralized hardware and software architecture of multi-robot control system.On this basis,the consensus plugin,smart contract and decentralized multi-robot control algorithm were designed to achieve decentralization.The experimental results of consensus of spherical amphibious multi-robot showed the effectiveness of the decentralization.     

Review: Milking robot utilization,a successful precision livestock farming evolution

Automatic milking systems (AMS), one of the earliest precision livestock farming developments, have revolutionized dairy farming around the world. While robots control the milking process, there have also been numerous changes to how the whole farm system is managed. Milking is no longer performed in defined sessions; rather, the cow can now choose when to be milked in AMS, allowing milking to be distributed throughout a 24 h period. Despite this ability, there has been little attention given to milking robot utilization across 24 h. In order to formulate relevant research questions and improve farm AMS management there is a need to determine the current knowledge gaps regarding the distribution of robot utilization. Feed, animal and management factors and their interplay on levels of milking robot utilization across 24 h for both indoor and pasture-based systems are here reviewed. The impact of the timing, type and quantity of feed offered and their interaction with the distance of feed from the parlour; herd social dynamics, climate and various other management factors on robot utilization through 24 h are provided. This novel review draws together both the opportunities and challenges that exist for farm management to use these factors to improved system efficiency and those that exist for further research.     

An Efficient Gait-generating Method for Electrical Quadruped Robot Based on Humanoid Power Planning Approach

The research field of legged robots has always relied on the bionic robotic research,especially in locomotion regulating approaches,such as foot trajectory planning,body stability regulating and energy efficiency prompting.Minimizing energy consumption and keeping the stability of body are considered as two main characteristics of human walking.This work devotes to develop an energy-efficient gait control method for electrical quadruped robots with the inspiration of human walking pattern.Based on the mechanical power distribution trend,an efficient humanoid power redistribution approach is established for the electrical quadruped robot.Through studying the walking behavior acted by mankind,such as the foot trajectory and change of mechanical power,we believe that the proposed controller which includes the bionic foot movement trajectory and humanoid power redistribution method can be implemented on the electrical quadruped robot prototype.The stability and energy efficiency of the proposed controller are tested by the simulation and the single-leg prototype experi-ment.The results verify that the humanoid power planning approach can improve the energy efficiency of the electrical quadruped robots.     

Designing an assistive robot for older adults: The ROBADOM project

ObjectiveThe ROBADOM project was devoted to the design of a “robot butler”, capable of providing verbal and non-verbal interactions and feedbacks for assisting older adults at home. In this article we focused on the following issues: (1) study the social context for designing social robot; define the robot appearance and investigate the perceptions and attitudes of older adults towards an assistive robot; (2) examine the perception of the expressivity of the robot, the social signals showing the end-user engagement level and the role of agent embodiment during the interaction between older adults and a robot.MethodThe design of the studies involved both qualitative and experimental methods.Results & DiscussionSmall robots with some traits between human/animal and machine were appreciated by the participants. As regards services, cognitive stimulation, reminder and object localization were positively rated. Although the participants considered an assistive robot as useful, they were not yet ready to adopt it. The expressions of the robot were perceived differently in older and young adults. Thus, a robotic system dedicated to older adults should be tailored to the specific characteristics of this population. We also identified social signals as indicators of the user's engagement level during interaction. Finally, the issue of the added valued of a robotic system in comparison to a laptop was raised by our participants. Therefore, various issues (technological development, human-robot interaction, social context…) are to be explored before testing the impact of the robot at home.     

A Bayesian Model of the Uncanny Valley Effect for Explaining the Effects of Therapeutic Robots in Autism Spectrum Disorder

One of the core features of autism spectrum disorder (ASD) is impaired reciprocal social interaction, especially in processing emotional information. Social robots are used to encourage children with ASD to take the initiative and to interact with the robotic tools to stimulate emotional responses. However, the existing evidence is limited by poor trial designs. The purpose of this study was to provide computational evidence in support of robot-assisted therapy for children with ASD. We thus propose an emotional model of ASD that adapts a Bayesian model of the uncanny valley effect, which holds that a human-looking robot can provoke repulsion and sensations of eeriness. Based on the unique emotional responses of children with ASD to the robots, we postulate that ASD induces a unique emotional response curve, more like a cliff than a valley. Thus, we performed numerical simulations of robot-assisted therapy to evaluate its effects. The results showed that, although a stimulus fell into the uncanny valley in the typical condition, it was effective at avoiding the uncanny cliff in the ASD condition. Consequently, individuals with ASD may find it more comfortable, and may modify their emotional response, if the robots look like deformed humans, even if they appear “creepy” to typical individuals. Therefore, we suggest that our model explains the effects of robot-assisted therapy in children with ASD and that human-looking robots may have potential advantages for improving social interactions in ASD.     

Control of a Quadruped Robot with Bionic Springy Legs in Trotting Gait

Legged robots have better performance on discontinuous terrain than that of wheeled robots. However, the dynamic trotting and balance control of a quadruped robot is still a challenging problem, especially when the robot has multi-joint legs. This paper presents a three-dimensional model of a quadruped robot which has 6 Degrees of Freedom （DOF） on torso and 5 DOF on each leg. On the basis of the Spring-Loaded Inverted Pendulum （SLIP） model, body control algorithm is discussed in the first place to figure out how legs work in 3D trotting. Then, motivated by the principle of joint function separation and introducing certain biological characteristics, two joint coordination approaches are developed to produce the trot and provide balance. The robot reaches the highest speed of 2.0 m.s-1, and keeps balance under 250 Kg.m.s-1 lateral disturbance in the simulations. The effectiveness of these approaches is also verified on a prototype robot which runs to 0.83 m.s-1 on the treadmill, The simulations and experiments show that legged robots have good biological properties, such as the ground reaction force, and spring-like leg behavior.     

Anthropomorphism or sub-anthropomorphism? An anthropological approach to gods and robots

Since the 1980s, a new area of research entitled HRI (Human-Robot Interaction) has been emerging in the field of robotic studies. It focuses on the empirical study of the relationship between robots and human beings. This article aims to contrast the findings of roboticists concerning the interaction between humans and robots with anthropological studies which focus on the ritual interaction between gods and humans in specific religious contexts. This idea may seem provocative, but it is argued here that such a comparison can yield valuable insights both at a theoretical level and at an empirical one. This will be demonstrated with reference to ritual interactions between humans and gods in the Western Himalayas.  

Résumé

Depuis les années 1980, un nouveau domaine d'étude appelé HRI (Human-Robot Interaction) est apparu dans la recherche en robotique. Il s'agit d'une étude empirique des relations entre robots et êtres humains. Le présent article met en regard les observations de roboticiens sur les interactions entre humains et robots et les études anthropologiques consacrées à l'interaction entre dieux et humains dans des contextes religieux spécifiques. Pour provocatrice qu'elle puisse paraître, cette comparaison peut constituer une approche intéressante, du point de vue théorique aussi bien qu'empirique. L'auteur le démontre en référence à des interactions rituelles entre hommes et dieux dans les massifs occidentaux de l'Himalaya.     

Empirical Study on Shapes of the Foot Pad and Walking Gaits for Water-Running Robots

Recently, various kinds ofbiomimetic robots have been studied. Among these biomimetic robots, water-running robots that mimic the characteristics of basilisk lizards have received much attention. However, studies on the performance with respect to different geometric parameters and gaits have been lacking. To run on the surface of water, a water-running robot needs suffi- cient force with high stability to stay above the water. We experimentally measured the performance of the foot pads with different geometric parameters and with various gaits. We measured and analyzed the forces in the vertical direction and rolling angles of five different foot pad shapes： a circular shape, square shape, half-spherical shape, open half-cylinder shape, and closed half-cylinder shape. Additionally, the rolling stabilities of three kinds of gaits： biped, trotting, and tripod, were also empirically analyzed. The results of this research can be used as a guideline to design a stable water-running robot.     

Can Machines Think? Interaction and Perspective Taking with Robots Investigated via fMRI

Background

When our PC goes on strike again we tend to curse it as if it were a human being. Why and under which circumstances do we attribute human-like properties to machines? Although humans increasingly interact directly with machines it remains unclear whether humans implicitly attribute intentions to them and, if so, whether such interactions resemble human-human interactions on a neural level. In social cognitive neuroscience the ability to attribute intentions and desires to others is being referred to as having a Theory of Mind (ToM). With the present study we investigated whether an increase of human-likeness of interaction partners modulates the participants'' ToM associated cortical activity.

Methodology/Principal Findings

By means of functional magnetic resonance imaging (subjects n = 20) we investigated cortical activity modulation during highly interactive human-robot game. Increasing degrees of human-likeness for the game partner were introduced by means of a computer partner, a functional robot, an anthropomorphic robot and a human partner. The classical iterated prisoner''s dilemma game was applied as experimental task which allowed for an implicit detection of ToM associated cortical activity. During the experiment participants always played against a random sequence unknowingly to them. Irrespective of the surmised interaction partners'' responses participants indicated having experienced more fun and competition in the interaction with increasing human-like features of their partners. Parametric modulation of the functional imaging data revealed a highly significant linear increase of cortical activity in the medial frontal cortex as well as in the right temporo-parietal junction in correspondence with the increase of human-likeness of the interaction partner (computerConclusions/SignificanceBoth regions correlating with the degree of human-likeness, the medial frontal cortex and the right temporo-parietal junction, have been associated with Theory-of-Mind. The results demonstrate that the tendency to build a model of another''s mind linearly increases with its perceived human-likeness. Moreover, the present data provides first evidence of a contribution of higher human cognitive functions such as ToM in direct interactions with artificial robots. Our results shed light on the long-lasting psychological and philosophical debate regarding human-machine interaction and the question of what makes humans being perceived as human.     

Concept of Intelligent Mechanical Design for Autonomous Mobile Robots

The concept of Intelligent Mechanical Design (IMD) is presented to show how a mechanical structure can be designed to affect robot controllability, simplification and task performance. Exploring this concept produces landmarks in the territory of mechanical robot design in the form of seven design principles. The design principles, which we call the Mecha-Telligence Principles (MTP), provide guidance on how to design mechanics for autonomous mobile robots. These principles guide us to ask the right questions when investigating issues concerning self-controllable, reliable, feasible, and compatible mechanics for autonomous mobile robots. To show how MTP can be applied in the design process we propose a novel methodology, named as Mecha-Telligence Methodology (MTM). Mechanical design by the proposed methodology is based on preference classification of the robot specification described by interaction of the robot with its environment and the physical parameters of the robot mechatronics. After defining new terms, we investigate the feasibility of the proposed methodology to the mechanical design of an autonomous mobile sewer inspection robot. In this industrial project we show how a passive-active intelligent moving mechanism can be designed using the MTM and employed in the field.     

Initial Development of a Novel Amphibious Robot with Transformable Fin-Leg Composite Propulsion Mechanisms

Amphibious robots are very attractive for their broad applications in resource exploration, disaster rescue, and recon- naissance. However, it is very challenging to develop the robots for their complex, amphibious working environments. In the complex amphibious environment, amphibious robots should possess multi-capabilities to walk on rough ground, maneuver underwater, and pass through transitional zones such as sandy and muddy terrain. These capabilities require a high-performance propulsion mechanism for the robots. To tackle a complex task, a novel amphibious robot （AmphiHex-I） with,transformable fin-leg composite propulsion mechanisms is developed. With the fin-leg composite propulsions, AmphiHex-I can walk on rough and soft substrates and swim in water with many maneuvers. This paper presents the structural design of the transformable fin-leg propulsion mechanism and its driving module. A hybrid model is used to explore the dynamics between the trans- formable legs and transitional environment such as granular medium. The locomotion performances of legs with various ellip- tical shapes are analyzed, which is verified by the coincidence between the model predictions and the simulation results. Further, an orthogonal experiment is conducted to study the locomotion performance of a two-legged platform walking with an asyn- chronous gait in the sandy and muddy terrain. Finally, initial experiments of AmphiHex-I walking on various lands and swimming in water are implemented. These results verify that the transformable fin-leg mechanisms enable the amphibious robot to pass through a complex, amphibious working environment.     

What Are You or Who Are You? The Emergence of Social Interaction between Dog and an Unidentified Moving Object (UMO)

Robots offer new possibilities for investigating animal social behaviour. This method enhances controllability and reproducibility of experimental techniques, and it allows also the experimental separation of the effects of bodily appearance (embodiment) and behaviour. In the present study we examined dogs’ interactive behaviour in a problem solving task (in which the dog has no access to the food) with three different social partners, two of which were robots and the third a human behaving in a robot-like manner. The Mechanical UMO (Unidentified Moving Object) and the Mechanical Human differed only in their embodiment, but showed similar behaviour toward the dog. In contrast, the Social UMO was interactive, showed contingent responsiveness and goal-directed behaviour and moved along varied routes. The dogs showed shorter looking and touching duration, but increased gaze alternation toward the Mechanical Human than to the Mechanical UMO. This suggests that dogs’ interactive behaviour may have been affected by previous experience with typical humans. We found that dogs also looked longer and showed more gaze alternations between the food and the Social UMO compared to the Mechanical UMO. These results suggest that dogs form expectations about an unfamiliar moving object within a short period of time and they recognise some social aspects of UMOs’ behaviour. This is the first evidence that interactive behaviour of a robot is important for evoking dogs’ social responsiveness.