Further explorations in evolutionary humanoid robotics

The field of evolutionary humanoid robotics is a branch of evolutionary robotics specifically dealing with the application of evolutionary principles to humanoid robot design. Previous studies demonstrated the possible future potential of this approach by evolving walking behaviors for simulated humanoid robots with up to 20 degrees of freedom. In this paper we examine further the evolutionary process by looking at the changes in diversity over time. We then investigate the effect of the immobilization of an individual joint or joints in the robot. The latter study may be of potential future use in prosthetic design. We also explore the possibility of the evolution of humanoid robots which can cope with different environmental conditions. These include reduced ground friction (ice) and modified gravitation (moon walking). We present initial results on the implementation of our simulated humanoid robots in hardware using the Bioloid robotic platform, using a model of this robot in order to evolve the desired motion patterns, for subsequent transfer to the real robot. We finish the article with a summary and brief discussion of future work. This work was presented in part at the 12th International Symposium on Artificial Life and Robotics, Oita, Japan, January 25–27, 2007     

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.     

Analysis of autonomous cooperative assembly using coordination schemes by heterogeneous robots using a control basis approach

Robotic technology is quickly evolving allowing robots to perform more complex tasks in less structured environments with more flexibility and autonomy. Heterogeneous multi-robot teams are more common as the specialized abilities of individual robots are used in concert to achieve tasks more effectively and efficiently. An important area of research is the use of robot teams to perform modular assemblies. To this end, this paper analyzed the relative performance of two robots with different morphologies and attributes in performing an assembly task autonomously under different coordination schemes using force sensing through a control basis approach. A rigid, point-to-point manipulator and a dual-armed pneumatically actuated humanoid robot performed the assembly of parts under a traditional “push-hold” coordination scheme and a human-mimicked “push-push” scheme. The study revealed that the scheme with higher level of cooperation—the “push-push” scheme—performed assemblies faster and more reliably, lowering the likelihood of stiction phenomena, jamming, and wedging. The study also revealed that in “push-hold” schemes industrial robots are better pushers and compliant robots are better holders. The results of our study affirm the use of heterogeneous robots to perform hard-to-do assemblies and also encourage humans to function as holder’s when working in concert with a robot assistant for insertion tasks.     

Simulation model of general human and humanoid motion

In the last decade we have witnessed a rapid growth of Humanoid Robotics, which has already constituted an autonomous research field. Humanoid robots (or simply humanoids) are expected in all situations of humans’ everyday life, “living” and cooperating with us. They will work in services, in homes, and hospitals, and they are even expected to get involved in sports. Hence, they will have to be capable of doing diverse kinds of tasks. This forces the researchers to develop an appropriate mathematical model to support simulation, design, and control of these systems. Another important fact is that today’s, and especially tomorrow’s, humanoid robots will be more and more humanlike in their shape and behavior. A dynamic model developed for an advanced humanoid robot may become a very useful tool for the dynamic analysis of human motion in different tasks (walking, running and jumping, manipulation, various sports, etc.). So, we derive a general model and talk about a human-and-humanoid simulation system. The basic idea is to start from a human/humanoid considered as a free spatial system (“flier”). Particular problems (walking, jumping, etc.) are then considered as different contact tasks – interaction between the flier and various objects (being either single bodies or separate dynamic systems).     

A Real-Time Hybrid Architecture for Biped Humanoids with Active Vision Mechanisms

A real-time hybrid control architecture for biped humanoid robots is proposed. The architecture is modular and hierarchical. The main robot’s functionalities are organized in four parallel modules: perception, actuation, world-modeling, and hybrid control. Hybrid control is divided in three behavior-based hierarchical layers: the planning layer, the deliberative layer, and the reactive layer, which work in parallel and have very different response speeds and planning capabilities. The architecture allows: (1) the coordination of multiple robots and the execution of group behaviors without disturbing the robot’s reactivity and responsivity, which is very relevant for biped humanoid robots whose gait control requires real-time processing. (2) The straightforward management of the robot’s resources using resource multiplexers. (3) The integration of active vision mechanisms in the reactive layer under control of behavior-dependant value functions from the deliberative layer. This adds flexibility in the implementation of complex functionalities, such as the ones required for playing soccer in robot teams. The architecture is validated using simulated and real Nao humanoid robots. Passive and active behaviors are tested in simulated and real robot soccer setups. In addition, the ability to execute group behaviors in real- time is tested in international robot soccer competitions.     

Development of flexible joints for a humanoid robot that walks on an oscillating plane

In this study, we develop flexible joints for a humanoid robot that walks on an oscillating plane and discuss their effectiveness in compensating disturbances. Conventional robots have a rigid frame and are composed of rigid joints driven by geared motors. Therefore, disturbances, which may be caused by external forces from other robots, obstacles, vibration and oscillation of the surface upon which the robot is walking, and so on, are transmitted directly to the robot body, causing the robot to fall. To address this problem, we focus on a flexible mechanism. We develop flexible joints and incorporate them in the waist of a humanoid robot; the experimental task of the robot is to walk on a horizontally oscillating plane until it reaches the desired position. The robot with the proposed flexible joints, reached the goal position despite the fact that the controller was the same as that used for a conventional robot walking on a static plane. From these results, we conclude that our proposed mechanism is effective for humanoid robots that walk on an oscillating plane.     

A closed-loop approach for tracking a humanoid robot using particle filtering and depth data

Humanoid robots introduce instabilities during biped march that complicate the process of estimating their position and orientation along time. Tracking humanoid robots may be useful not only in typical applications such as navigation, but in tasks that require benchmarking the multiple processes that involve registering measures about the performance of the humanoid during walking. Small robots represent an additional challenge due to their size and mechanic limitations which may generate unstable swinging while walking. This paper presents a strategy for the active localization of a humanoid robot in environments that are monitored by external devices. The problem is faced using a particle filter method over depth images captured by an RGB-D sensor in order to effectively track the position and orientation of the robot during its march. The tracking stage is coupled with a locomotion system controlling the stepping of the robot toward a given oriented target. We present an integral communication framework between the tracking and the locomotion control of the robot based on the robot operating system, which is capable of achieving real-time locomotion tasks using a NAO humanoid robot.     

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.     

Policy gradient learning for a humanoid soccer robot

In humanoid robotic soccer, many factors, both at low-level (e.g., vision and motion control) and at high-level (e.g., behaviors and game strategies), determine the quality of the robot performance. In particular, the speed of individual robots, the precision of the trajectory, and the stability of the walking gaits, have a high impact on the success of a team. Consequently, humanoid soccer robots require fine tuning, especially for the basic behaviors. In recent years, machine learning techniques have been used to find optimal parameter sets for various humanoid robot behaviors. However, a drawback of learning techniques is time consumption: a practical learning method for robotic applications must be effective with a small amount of data. In this article, we compare two learning methods for humanoid walking gaits based on the Policy Gradient algorithm. We demonstrate that an extension of the classic Policy Gradient algorithm that takes into account parameter relevance allows for better solutions when only a few experiments are available. The results of our experimental work show the effectiveness of the policy gradient learning method, as well as its higher convergence rate, when the relevance of parameters is taken into account during learning.     

Effects of lateral head tilt on user perceptions of humanoid and android robots

Human responses to android and humanoid robots have become an important topic to social scientists due to the increasing prevalence of social and service robots in everyday life. The present research connects work on the effects of lateral (sideward) head tilts, an eminent feature of nonverbal human behavior, to the experience of android and humanoid robots. In two experiments (N = 402; N = 253) the influence of lateral head tilts on user perceptions of android and humanoid robots were examined. Photo portrayals of three different robots (Asimo, Kojiro, Telenoid) were manipulated. The stimuli included head tilts of −20°, −10° (left tilt), +10°, +20° (right tilt) and 0° (upright position). Compared to an upright head posture, we found higher scores for attributed human likeness, cuteness, and spine-tinglingness when the identical robots conveyed a head tilt. Results for perceived warmth, eeriness, attractiveness, and dominance varied with the robot or head tilts yielded no effects. Implications for the development and marketing of android and humanoid robots are discussed.     

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.     

双足机器人HEUBR-1 样机研制与实验研究

模拟人的肌肉驱动方式,为双足机器人HEUBR-1 设计了二自由度的空间并联机构,并将其应用于双 足机器人HEUBR-1 下肢关节,实现了一种新的串并混联的仿人下肢结构．在HEUBR-1 的足部增加了足趾关节,使 机器人能够模拟人的行走方式,实现真正的拟人步态行走．阐述了双足机器人HEUBR-1 稳定拟人行走的关键性技 术,提出了综合稳定性判据,分析了拟人的多种步态．通过拟人行走步态实验分析,验证了双足机器人HEUBR-1 串 并混联的仿人结构的设计合理性及拟人步态分析的准确性．     

Pivoting based manipulation by a humanoid robot

In this paper we address whole-body manipulation of bulky objects by a humanoid robot. We adopt a “pivoting” manipulation method that allows the humanoid to displace an object without lifting, but by the support of the ground contact. First, the small-time controllability of pivoting is demonstrated. On its basis, an algorithm for collision-free pivoting motion planning is established taking into account the naturalness of motion as nonholonomic constraints. Finally, we present a whole-body motion generation method by a humanoid robot, which is verified by experiments.     

Walking Control Algorithm of Biped Humanoid Robot on Uneven and Inclined Floor

This paper describes walking control algorithm for the stable walking of a biped humanoid robot on an uneven and inclined floor. Many walking control techniques have been developed based on the assumption that the walking surface is perfectly flat with no inclination. Accordingly, most biped humanoid robots have performed dynamic walking on well designed flat floors. In reality, however, a typical room floor that appears to be flat has local and global inclinations of about 2°. It is important to note that even slight unevenness of a floor can cause serious instability in biped walking robots. In this paper, the authors propose an online control algorithm that considers local and global inclinations of the floor by which a biped humanoid robot can adapt to the floor conditions. For walking motions, a suitable walking pattern was designed first. Online controllers were then developed and activated in suitable periods during a walking cycle. The walking control algorithm was successfully tested and proved through walking experiments on an uneven and inclined floor using KHR-2 (KAIST Humanoid robot-2), a test robot platform of our biped humanoid robot, HUBO.     

The Effect of a Humanoid Robot’s Emotional Behaviors on Users’ Emotional Responses: Evidence from Pupillometry and Electroencephalography Measures

ABSTRACT

The design of humanoid robots’ emotional behaviors has attracted many scholars’ attention. However, users’ emotional responses to humanoid robots’ emotional behaviors which differ from robots’ traditional behaviors remain well understood. This study aims to investigate the effect of a humanoid robot’s emotional behaviors on users’ emotional responses using subjective reporting, pupillometry, and electroencephalography. Five categories of the humanoid robot’s emotional behaviors expressing joy, fear, neutral, sadness, or anger were designed, selected, and presented to users. Results show that users have a significant positive emotional response to the humanoid robot’s joy behavior and a significant negative emotional response to the humanoid robot’s sadness behavior, indicated by the metrics of reported valence and arousal, pupil diameter, frontal middle relative theta power, and frontal alpha asymmetry score. The results suggest that humanoid robot’s emotional behaviors can evocate users’ significant emotional response. The evocation might relate to the recognition of these emotional behaviors. In addition, the study provides a multimodal physiological method of evaluating users’ emotional responses to the humanoid robot’s emotional behaviors.     

柔性两轮直立式自平衡仿人机器人的建模及控制

研究了柔性两轮直立式自平衡仿人机器人的动力学建模问题．运用拉格朗日方法和动力学原理建立了柔性两轮自平衡仿人机器人的动力学模型．使用弹簧模仿人的腰椎,并考虑了机器人的柔性腰椎弯曲;这是与以前机器人的不同之处．对得到的动力学模型进行了线性化处理,并建立其状态空间方程;由此建立的动力学模型结构简单,易于对机器人进行有效控制．仿真实验验证了系统的稳定性,对其实验结果进行的详细分析验证了系统建模和LQR控制器设计的合理性和有效性．     

Human-and-Humanoid Postures Under External Disturbances: Modeling,Simulation, and Robustness. Part 1: Modeling

It is a well-known fact that the growth of technology has radically changed our approach to biosciences and medicine. What is interesting is that in the last decade we have witnessed a reverse influence—a trend towards “biologically inspired” solutions to technical problems. This leads to a true symbiosis between bio and technical sciences. A good example is the intersection and overlapping of three distinct fields: sports, medicine, and robotics. This paper intends to apply sophisticated methods developed for mathematical modeling of humanoid robots in real human motions, particularly in posture stabilization and selection of appropriate postures for different situation in sports and every day life. A general simulation system is realized: following a deductive principle, the algorithm considers particular human/humanoid motions (like those occurring in different sports) as being just special cases of a general motion and impact theory. Simulation includes the interaction with the environment. Simulating a human/humanoid dynamics in a given task, all relevant characteristics could be found: trajectories, velocities and accelerations, loads of joints, power requirements, energy consumption, contact forces including ground reactions, impact effects, etc. Simulation is used in solving a problem that is important for both humans and humanoid robots, namely, the behavior of a posture (keeping stability or collapsing) when subject to different disturbances. Although “posture” is mainly a static term, maintaining its balance in the presence of disturbances is a truly dynamic problem. Typical postures from every day life and sports are considered, such as: upright standing, squat (and partial squat), and three karate postures. Two sorts of disturbances are applied to eventually, compromise the posture: external impulse and permanent external force. This paper does not aim to suggest some new control strategy but to develop the dynamic model and simulation algorithm, and apply them to compare the robustness of different postures to external disturbances.     

Imitation learning of humanoid locomotion using the direction of landing foot

Since it is quite difficult to create motions for humanoid robots having a fairly large number of degrees of freedom, it would be very convenient indeed if robots could observe and imitate what they want to create. To this end, this paper discusses how humanoid robots can learn through imitation taking into consideration the fact that demonstrator and imitator robots may have different kinematics and dynamics. As part of a wider interest in humanoid motion generation in general, this work mainly investigates how imitator robots adapt a reference locomotion gait copied from a demonstrator robot. Specifically, the self-adjusting adaptor is proposed, where the perceived locomotion pattern is modified to keep the direction of the lower leg contacting the ground identical between the demonstrator and the imitator, and to sustain dynamic stability by controlling the position of the center of mass. The validity of the proposed scheme is verified through simulations on OpenHRP and real experiments. Recommended by Editorial Board member Hyoukryeol Choi under the direction of Editor Jae-Bok Song. This work was conducted as a program for the “Fostering Talent in Emergent Research Fields” in Special Coordination Funds for the Promotion of Science and Technology by the Ministry of Education, Culture, Sports, Science and Technology of Japan. This work was also supported in part by MIC and IITA of Korea through IT Leading R&D Support Project. [2009-S028-01, Development of Cooperative Network-based Humanoids Technology] Woosung Yang received his B.S. and M.S. degrees in Mechanical Engineering from Sogang University, Seoul, Korea in 2001 and 2003, and his Ph.D. degree in the School of Information Science from Japan Advanced Institute of Science and Technology (JAIST), Ishikawa, Japan in 2007, respectively. Since 2007, he has been a Post-doctoral Researcher in Center for Cognitive Robotics, Korea Institute of Science and Technology. His research interests include intelligent control theory, biologically inspired control and system, humanoids, and actuator controls for small form factor precision devices. Nak Young Chong received his B.S., M.S., and Ph.D. in Mechanical Engineering from Hanyang University, Seoul, Korea in 1987, 1989, and 1994, respectively. He was senior researcher at Daewoo Heavy Industries Ltd. (1994–98), visiting researcher at MEL in Tsukuba, Japan (1995–96), and postdoctoral researcher at KIST (1998). From 1998–2007, he was on the research staff of AIST in Tsukuba, Japan. In 2003, he joined the faculty of JAIST as Associate Professor of Information Science. Dr. Chong served as Co-chair of the IEEE RAS Technical Committee on Networked Robots (2004–06), and the Fujitsu Scientific Systems Robotics WG (2004–06) and Robot Information Processing WG (2006–08), respectively. He visited Northwestern University (2001) and Georgia Tech (2008–09). He is currently serving as Associate Editor of the IEEE Transactions on Robotics and the International Journal of Assistive Robotics and Systems. He is the Korea Robotics Society director of international cooperation, and a member of IEEE, RSJ, and SICE.     

人体步行规律与仿人机器人步态规划

从仿生学角度分析了人体的步行运动规律,提出了一种基于人体运动规律的仿人机器人步态参数设定方法.首先对人体步行运动数据进行捕捉并分析,得出人体各步态参数间的函数关系,以人体步行相似性作为评价指标,提出仿人机器人步态参数的设定方法.其次,通过分析人体在步行过程中的补偿支撑脚偏航力矩的基本原理,提出了基于双臂及腰关节协调运动的仿人机器人偏航力矩补偿算法,以提高仿人机器人行走的稳定性.最后通过仿真及实验验证了所提出的步态规划方法的正确性及有效性.     

Control of underactuated planar pronking through an embedded spring-mass Hopper template

Autonomous use of legged robots in unstructured, outdoor settings requires dynamically dexterous behaviors to achieve sufficient speed and agility without overly complex and fragile mechanics and actuation. Among such behaviors is the relatively under-studied pronking (aka. stotting), a dynamic gait in which all legs are used in synchrony, usually resulting in relatively slow speeds but long flight phases and large jumping heights. Instantiations of this gait for robotic systems have been mostly limited to open-loop strategies, suffering from severe pitch instability for underactuated designs due to the lack of active feedback. However, both the kinematic simplicity of this gait and its dynamic nature suggest that the Spring-Loaded Inverted Pendulum model (SLIP) would be a good basis for the implementation of a more robust feedback controller for pronking. In this paper, we describe how template-based control, a controller structure based on the embedding of a simple dynamical “template” within a more complex “anchor” system, can be used to achieve very stable pronking for a planar, underactuated hexapod robot. In this context, high-level control of the gait is regulated through speed and height commands to the SLIP template, while the embedding controller ensures the stability of the remaining degrees of freedom. We use simulation studies to show that unlike existing open-loop alternatives, the resulting control structure provides explicit gait control authority and significant robustness against sensor and actuator noise.