Designing a sociable humanoid robot for interdisciplinary research

This paper presents the humanoid robot BARTHOC and the smaller, but system-equal twin, BARTHOC Junior. Both robots have been developed to study human–robot interaction. The main focus of BARTHOC's design was to realize the expression and behavior of the robot to be as human-like as possible. This allows us to apply the platform to manifold research and demonstration areas. With its human-like look and mimic possibilities it differs from other platforms like ASIMO or QRIO and enables experiments even close to Mori's 'uncanny valley'. The paper describes details of the mechanical and electrical design of BARTHOC together with its PC control interface and an overview of the interaction architecture. Its humanoid appearance allows limited imitation of human behavior. The basic interaction software running on BARTHOC has been completely ported from a mobile robot except for some functionalities that could not be used due to hardware differences such as the lack of mobility. Based on these components, the robot's human-like appearance will enable us to study embodied interaction and to explore theories of human intelligence.     

Learning to Acquire Whole-Body Humanoid Center of Mass Movements to Achieve Dynamic Tasks

This paper presents a novel approach for acquiring dynamic whole-body movements on humanoid robots focused on learning a control policy for the center of mass (CoM). In our approach, we combine both a model-based CoM controller and a model-free reinforcement learning (RL) method to acquire dynamic whole-body movements in humanoid robots. (i) To cope with high dimensionality, we use a model-based CoM controller as a basic controller that derives joint angular velocities from the desired CoM velocity. The balancing issue can also be considered in the controller. (ii) The RL method is used to acquire a controller that generates the desired CoM velocity based on the current state. To demonstrate the effectiveness of our approach, we apply it to a ball-punching task on a simulated humanoid robot model. The acquired whole-body punching movement was also demonstrated on Fujitsu's Hoap-2 humanoid robot.     

Generating human-like soccer primitives from human data

Recently, interest in analysis and generation of human and human-like motion has increased in various areas. In robotics, in order to operate a humanoid robot, it is necessary to generate motions that have strictly dynamic consistency. Furthermore, human-like motion for robots will bring advantages such as energy optimization.This paper presents a mechanism to generate two human-like motions, walking and kicking, for a biped robot using a simple model based on observation and analysis of human motion. Our ultimate goal is to establish a design principle of a controller in order to achieve natural human-like motions. The approach presented here rests on the principle that in most biological motor learning scenarios some form of optimization with respect to a physical criterion is taking place. In a similar way, the equations of motion for the humanoid robot systems are formulated in such a way that the resulting optimization problems can be solved reliably and efficiently.The simulation results show that faster and more accurate searching can be achieved to generate an efficient human-like gait. Comparison is made with methods that do not include observation of human gait. The gait has been successfully used to control Robo-Erectus, a soccer-playing humanoid robot, which is one of the foremost leading soccer-playing humanoid robots in the RoboCup Humanoid League.     

Interactive Humanoid Robots for a Science Museum

One objective of the Intelligent Robotics and Communication Laboratories is to develop an intelligent communication robot that supports people in an open everyday environment by interacting with them. A humanoid robot can help achieve this objective because its physical structure lets it interact through human-like body movements such as shaking hands, greeting, and pointing. Both adults and children are more likely to understand such interactions than interactions with an electronic interface such as a touch panel or buttons. To behave intelligently during an interaction, a robot requires many types of information about its environment and the people with whom it interacts. However, in open everyday environments, simple recognition functions such as identifying an individual are difficult because the presence and movement of a large number of people as well as unfavorable illumination and background conditions affect the robot's sensing ability. We integrated humanoid robots and ubiquitous sensors in an autonomous system to assist visitors at an Osaka Science Museum exhibit     

Robot Catching: Towards Engaging Human-Humanoid Interaction

Our focus is on creating interesting and human-like behaviors for humanoid robots and virtual characters. Interactive behaviors are especially engaging. They are also challenging, as they necessitate finding satisfactory realtime solutions for complex systems such as the 30-degree-of-freedom humanoid robot in our laboratory. Here we describe a catching behavior between a person and a robot. We generate ball-hand impact predictions based on the flight of the ball, and human-like motion trajectories to move the hand to the catch position. We use a dynamical systems approach to produce the motion trajectories where new movements are generated from motion primitives as they are needed.     

机器人的CP-nets优化类人轨迹规划

机器人移动轨迹按照人的手臂来模拟是提高机器人安全性和人机交互能力的有效方法,特别是针对机器人抓取路径不唯一的场合,类人行为对于人机系统表现更加自然。此前,通常利用Kinect等设备,基于人工神经网络和K近邻算法等智能算法对类人轨迹进行规划,但无法获得未采样过的最优轨迹。本文基于CP-nets采用偏好模型研究类人运动轨迹,然后将该模型应用于机器人控制,在没有采样的情况下,也可得到最优的类人轨迹。实验结果表明,基于CP-nets 的类人规划轨迹具有较高的效率和舒适性,符合人的运动特征。     

Human-Oriented Interaction With an Anthropomorphic Robot

A very important aspect in developing robots capable of human-robot interaction (HRI) is the research in natural, human-like communication, and subsequently, the development of a research platform with multiple HRI capabilities for evaluation. Besides a flexible dialog system and speech understanding, an anthropomorphic appearance has the potential to support intuitive usage and understanding of a robot, e.g., human-like facial expressions and deictic gestures can as well be produced and also understood by the robot. As a consequence of our effort in creating an anthropomorphic appearance and to come close to a human- human interaction model for a robot, we decided to use human-like sensors, i.e., two cameras and two microphones only, in analogy to human perceptual capabilities too. Despite the challenges resulting from these limits with respect to perception, a robust attention system for tracking and interacting with multiple persons simultaneously in real time is presented. The tracking approach is sufficiently generic to work on robots with varying hardware, as long as stereo audio data and images of a video camera are available. To easily implement different interaction capabilities like deictic gestures, natural adaptive dialogs, and emotion awareness on the robot, we apply a modular integration approach utilizing XML-based data exchange. The paper focuses on our efforts to bring together different interaction concepts and perception capabilities integrated on a humanoid robot to achieve comprehending human-oriented interaction.     

How far away is “artificial man”

The authors claim that a careful examination of robotics science and technology from its origins in the 1950s to its current status reveals that such progress, albeit very important, profitable, and with a strong impact on society, was basically the “side activities” to the ever-existing and continuous desire of mankind to build and realize humanoid robots, artificial men equipped uith proper intelligence capable of operating autonomously, thus replacing trained individuals for dexterous jobs. They consider such a humanoid robot through the realistic tasks/jobs it will most probably do. It is postulated that this humanoid robot be considered as a personal helper (a home robot or personal robot). Given the present level of technology, the question is posed: are we ready to move towards personal robotics, and what might be the first step? A possible answer to this question is given through a discussion of the human-like characteristics a personal robot must have; namely, human-like motion, human-like intelligence, and human-like communication     

Motion planning for humanoid robots based on virtual constraints extracted from recorded human movements

In the field of robotics there is a great interest in developing strategies and algorithms to reproduce human-like behavior. In this paper, we consider motion planning for humanoid robots based on the concept of virtual holonomic constraints. At first, recorded kinematic data of particular human motions are analyzed in order to extract consistent geometric relations among various joint angles defining the instantaneous postures. Second, a simplified human body representation leads to dynamics of an underactuated mechanical system with parameters based on anthropometric data. Motion planning for humanoid robots of similar structure can be carried out by considering solutions of reduced dynamics obtained by imposing the virtual holonomic constraints that are found in human movements. The relevance of such a reduced mathematical model in accordance with the real human motions under study is shown. Since the virtual constraints must be imposed on the robot dynamics by feedback control, the design procedure for a suitable controller is briefly discussed.     

Inverse Kinematics Based Human Mimicking System using Skeletal Tracking Technology

Humanoid robots needs to have human-like motions and appearance in order to be well-accepted by humans. Mimicking is a fast and user-friendly way to teach them human-like motions. However, direct assignment of observed human motions to robot’s joints is not possible due to their physical differences. This paper presents a real-time inverse kinematics based human mimicking system to map human upper limbs motions to robot’s joints safely and smoothly. It considers both main definitions of motion similarity, between end-effector motions and between angular configurations. Microsoft Kinect sensor is used for natural perceiving of human motions. Additional constraints are proposed and solved in the projected null space of the Jacobian matrix. They consider not only the workspace and the valid motion ranges of the robot’s joints to avoid self-collisions, but also the similarity between the end-effector motions and the angular configurations to bring highly human-like motions to the robot. Performance of the proposed human mimicking system is quantitatively and qualitatively assessed and compared with the state-of-the-art methods in a human-robot interaction task using Nao humanoid robot. The results confirm applicability and ability of the proposed human mimicking system to properly mimic various human motions.     

Modeling and design of a humanoid robotic face based on an active drive points model

This study develops a face robot with human-like appearance for making facial expressions similar to a specific subject. First, an active drive points (ADPs) model is proposed for establishing a robotic face with less active degree of freedom for bipedal humanoid robots. Then, a robotic face design method is proposed, with the robot possessing similar facial appearance and expressions to that of a human subject. A similarity evaluation method is presented to evaluate the similarity of facial expressions between a robot and a specific human subject. Finally, the proposed facial model and the design methods are verified and implemented on a humanoid robot platform.     

Realization of sign language motion using a dual-arm/hand humanoid robot

The recent increase in technological maturity has empowered robots to assist humans and provide daily services. Voice command usually appears as a popular human–machine interface for communication. Unfortunately, deaf people cannot exchange information from robots through vocal modalities. To interact with deaf people effectively and intuitively, it is desired that robots, especially humanoids, have manual communication skills, such as performing sign languages. Without ad hoc programming to generate a particular sign language motion, we present an imitation system to teach the humanoid robot performing sign languages by directly replicating observed demonstration. The system symbolically encodes the information of human hand–arm motion from low-cost depth sensors as a skeleton motion time-series that serves to generate initial robot movement by means of perception-to-action mapping. To tackle the body correspondence problem, the virtual impedance control approach is adopted to smoothly follow the initial movement, while preventing potential risks due to the difference in the physical properties between the human and the robot, such as joint limit and self-collision. In addition, the integration of the leg-joints stabilizer provides better balance of the whole robot. Finally, our developed humanoid robot, NINO, successfully learned by imitation from human demonstration to introduce itself using Taiwanese Sign Language.     

Expressing and interpreting emotional movements in social games with robots

This paper provides a framework for recording, analyzing and modeling of 3 dimensional emotional movements for embodied game applications. To foster embodied interaction, we need interfaces that can develop a complex, meaningful understanding of intention—both kinesthetic and emotional—as it emerges through natural human movement. The movements are emulated on robots or other devices with sensory-motor features as a part of games that aim improving the social interaction skills of children. The design of an example game platform that is used for training of children with autism is described since the type of the emotional behaviors depends on the embodiment of the robot and the context of the game. The results show that quantitative movement parameters can be matched to emotional state of the embodied agent (human or robot) using the Laban movement analysis. Emotional movements that were emulated on robots using this principle were tested with children in the age group 7–9. The tests show reliable recognition on most of the behaviors.     

Communicating emotions and mental states to robots in a real time parallel framework using Laban movement analysis

This paper presents a parallel real time framework for emotions and mental states extraction and recognition from video fragments of human movements. In the experimental setup human hands are tracked by evaluation of moving skin-colored objects. The tracking analysis demonstrates that acceleration and frequency characteristics of the traced objects are relevant for classification of the emotional expressiveness of human movements. The outcomes of the emotional and mental states recognition are cross-validated with the analysis of two independent certified movement analysts (CMA’s) who use the Laban movement analysis (LMA) method. We argue that LMA based computer analysis can serve as a common language for expressing and interpreting emotional movements between robots and humans, and in that way it resembles the common coding principle between action and perception by humans and primates that is embodied by the mirror neuron system. The solution is part of a larger project on interaction between a human and a humanoid robot with the aim of training social behavioral skills to autistic children with robots acting in a natural environment.     

Cooperative embodied communication emerged by interactive humanoid robots

Research on humanoid robots has produced various uses for their body properties in communication. In particular, mutual relationships of body movements between a robot and a human are considered to be important for smooth and natural communication, as they are in human–human communication. We have developed a semi-autonomous humanoid robot system that is capable of cooperative body movements with humans using environment-based sensors and switching communicative units. Concretely, this system realizes natural communication by using typical behaviors such as: “nodding,” “eye-contact,” “face-to-face,” etc. It is important to note that the robot parts are NOT operated directly; only the communicative units in the robot system are switched. We conducted an experiment using the mentioned robot system and verified the importance of cooperative behaviors in a route-guidance situation where a human gives directions to the robot. The task requires a human participant (called the “speaker”) to teach a route to a “hearer” that is (1) a human, (2) a developed robot that performs cooperative movements, and (3) a robot that does not move at all. This experiment is subjectively evaluated through a questionnaire and an analysis of body movements using three-dimensional data from a motion capture system. The results indicate that the cooperative body movements greatly enhance the emotional impressions of human speakers in a route-guidance situation. We believe these results will allow us to develop interactive humanoid robots that sociably communicate with humans.     

基于运动相似性的仿人机器人双足步行研究

提出了一种基于人体步行运动相似性的仿人机器人双足步行动作设计方法．改进了人体步行轨迹的参 数获取与相似性匹配系统,扩展了相似性函数的适用范围．根据仿人机器人的机械连杆特点定义了步行运动周期中 的关键姿势与子相变换,建立了运动学约束方程,并对行走中出现的动态稳定性问题进行了约束．仿真和实体机器 人实验验证了该方法的有效性．     

A new paradigm of humanoid robot motion programming based on touch interpretation

Most humanoid soccer robot teams design the basic movements of their robots, like walking and kicking, off-line and manually. Once these motions are considered satisfactory, they are stored in the robot’s memory and played according to a high level behavioral strategy. Much time is spent in the development of the movements, and despite the significant progress made in humanoid soccer robots, the interfaces employed for the development of motions are still quite primitive. In order to accelerate development, an intuitive instruction method is desired. We propose the development of robot motions through physical interaction. In this paper we propose a ”teaching by touching” approach; the human operator teaches a motion by directly touching the robot’s body parts like a dance instructor. Teaching by directly touching is intuitive for instructors. However, the robot needs to interpret the instructor’s intention since tactile communication can be ambiguous. This paper presents a method to learn the interpretation of the touch meaning and investigates, through experiments, a general (shared among different users) and intuitive touch manner.     

Effects of etiquette strategy on human–robot interaction in a simulated medicine delivery task

The objective of this study was to examine the extent to which a model of linguistic etiquette in human–human interaction could be applied to human–robot interaction (HRI) domain, and how different etiquette strategies proposed through the model might influence performance of humans and robots as mediated by manipulations of robot physical features, in a simulated medicine delivery task. A “wizard of Oz” experiment was conducted in which either a humanoid robot or a mechanical-looking robot was used to present medicine reminding utterances (following different etiquette strategies) to participants, who were engaged in a primary cognitive task (a Sudoku puzzle). Results revealed the etiquette model to partially extend to the HRI domain. Participants were not sensitive to positive language from robots (e.g., appreciation of human values/wants) and such a strategy did not succeed in supporting or enhancing the “positive face” of human users. Both “bald” (no linguistic courtesy) and mixed strategies (positive and “negative face” (minimizing user imposition) saving) resulted in moderate user perceived etiquette scores (PE). However, individual differences suggested such robot linguistic strategies should be applied with caution. Opposite to this, a negative face saving strategy (supporting user freedom of choice) promoted user task and robot performance (in terms of user response time to robot requests), and resulted in the highest PE score. There was also evidence that humanoid robot features provide additional social cues that may be used by patients and support human and robot performance, but not PE. These results provide a basis for determining appropriate etiquette strategies and robot appearance to promote better collaborative task performances for future health care delivery applications of service robots.     

Robot Head Motion Control with an Emphasis on Realism of Neck–Eye Coordination during Object Tracking

Important aspects of present-day humanoid robot research is to make such robots look realistic and human-like, both in appearance, as well as in motion and mannerism. In this paper, we focus our study on advanced control leading to realistic motion coordination for a humanoid’s robot neck and eyes while tracking an object. The motivating application for such controls is conversational robotics, in which a robot head “actor” should be able to detect and make eye contact with a human subject. Therefore, in such a scenario, the 3D position and orientation of an object of interest in space should be tracked by the redundant head–eye mechanism partly through its neck, and partly through its eyes. In this paper, we propose an optimization approach, combined with a real-time visual feedback to generate the realistic robot motion and robustify it. We also offer experimental results showing that the neck–eye motion obtained from the proposed algorithm is realistic comparing to the head–eye motion of humans.     

Communication capability of telepresence system with the miniature humanoid MH-2

Recently, several different types of telepresence robots have been developed. Their ability to communicate with a person in a remote location has been analyzed to achieve rich communication, including the presence of an operator. These studies focused on human-sized robots, small-sized non-humanoid robots, or small-sized humanoid robots without human-like proportions. A small-sized humanoid robot with human-like proportions has not been studied because of the absence of such a small humanoid. It should be noted that human-like proportions play a very important role in enhancing the presence of an operator through an avatar. In our previous work, a small-sized humanoid robot named MH-2 was developed for wearable telepresence system. The MH-2 consists of seven degrees-of-freedom (7-DOF) arms, a 3-DOF head, and a torso scaled according to human-like proportions. Wire–pulley mechanisms were employed to achieve a compact design to adopt a requirement for wearability. In this work, a telepresence system is introduced for the evaluation of the communication ability of the MH-2. In the experiment, Skype, using a flat display, was compared with the MH-2. The “Indian Poker” game was employed for the experiment. It is an ideal evaluation platform because it is a psychological game that requires careful observations among the players. The evaluations were conducted in terms of six aspects: emotion or personality, line of sight, familiarity, presence, enjoyment, and smoothness of the game progress. The experimental results showed that the MH-2 performed positively in two out of six aspects, namely the line of sight and smoothness of the game progress. On the other hand, facial expressions play important role to display individual presence. From a comprehensive standpoint, the MH-2 demonstrated good capabilities for rich remote communications.