Human-and-Humanoid Postures Under External Disturbances: Modeling,Simulation, and Robustness. Part 2: Simulation and Robustness

The sophisticated method for mathematical modeling of humanoid robots formulated in Part 1 of this paper is applied here to the dynamic task of keeping a posture under disturbance, which is equally important to humans and humanoid robots. The idea of this work is to develop and realize a simulator tool for dynamic analysis of human-or-humanoid behavior under disturbances. To show the potentials and verify this tool, we comparatively analyze the robustness of some postures to external disturbance. At this stage of research we do not conduct real experiments with humans/humanoids but try to verify our simulation tool by relying on available experience. Therefore, the postures for comparison are taken from everyday life and from sports: upright standing, squat posture, and three karate postures. As the external disturbance we choose an impulse and a permanent force, both with variable direction and magnitude.     

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).     

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.     

Evolutionary control of bipedal locomotion in a high degree-of-freedom humanoid robot: first steps

This article describes a methodology, together with an associated series of experiments employing this methodology, for the evolution of walking behavior in a simulated humanoid robot with up to 20 degrees of freedom. The robots evolved in this study learn to walk smoothly in an upright or near-upright position and demonstrate a variety of different locomotive behaviors, including “skating,” “limping,” and walking in a manner curiously reminiscent of a mildly or heavily intoxicated person. A previous study demonstrated the possible potential utility of this approach while evolving controllers based on simulated humanoid robots with a restricted range of movements. Although walking behaviors were developed, these were slow and relied on the robot walking in an excessively stooped position, similar to the gait of an infirm elderly person. This article extends the previous work to a robot with many degrees of freedom, up to 20 in total (arms, elbows, legs, hips, knees, etc.), and demonstrates the automatic evolution of fully upright bipedal locomotion in a humanoid robot using an accurate physics simulator. This work was presented in part at the 11th International Symposium on Artificial Life and Robotics, Oita, Japan, January 23–25, 2006     

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.     

Posture/Walking Control for Humanoid Robot Based on Kinematic Resolution of CoM Jacobian With Embedded Motion

This paper proposes the walking pattern generation method, the kinematic resolution method of center of mass (CoM) Jacobian with embedded motions, and the design method of posture/walking controller for humanoid robots. First, the walking pattern is generated using the simplified model for bipedal robot. Second, the kinematic resolution of CoM Jacobian with embedded motions makes a humanoid robot balanced automatically during movement of all other limbs. Actually, it offers an ability of whole body coordination to humanoid robot. Third, the posture/walking controller is completed by adding the CoM controller minus the zero moment point controller to the suggested kinematic resolution method. We prove that the proposed posture/walking controller brings the disturbance input-to-state stability for the simplified bipedal walking robot model. Finally, the effectiveness of the suggested posture/walking control method is shown through experiments with regard to the arm dancing and walking of humanoid robot.     

Dynamically-Stable Motion Planning for Humanoid Robots

We present an approach to path planning for humanoid robots that computes dynamically-stable, collision-free trajectories from full-body posture goals. Given a geometric model of the environment and a statically-stable desired posture, we search the configuration space of the robot for a collision-free path that simultaneously satisfies dynamic balance constraints. We adapt existing randomized path planning techniques by imposing balance constraints on incremental search motions in order to maintain the overall dynamic stability of the final path. A dynamics filtering function that constrains the ZMP (zero moment point) trajectory is used as a post-processing step to transform statically-stable, collision-free paths into dynamically-stable, collision-free trajectories for the entire body. Although we have focused our experiments on biped robots with a humanoid shape, the method generally applies to any robot subject to balance constraints (legged or not). The algorithm is presented along with computed examples using both simulated and real humanoid robots.     

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.     

Motion teaching method for complex robot links using motor current

Conventional robot motion teaching methods use a teaching pendant or a motion capture device and are not the most convenient or intuitive ways to teach a robot sophisticated and fluid movements such as martial arts motions. Ideally, a robot could be set up as if it were a clothing mannequin that has light limbs and flexible yet frictional joints which can be positioned at desirable shape and hold all the positions. To do the same with a robot, an operator could pull or push the links with minor forces until the desired robot posture is attained. For this, a robot should measure the applied external force by using torque sensors at the robot joints. However, torque sensors are bulky and expensive to install in every DOF joints while keeping a compact design, which is essential to humanoid robots. In this paper, we use only motor current readings to acquire joint torques. The equations used to compensate for the effect of gravity on the joint torques and the self-calibration method to earn link parameters are presented. Additionally, kinematic restrictions can be imposed on the robot’s arms to simplify the motion teaching. Here, we teach the Kendo training robot with this method and the robot’s learnt martial art motions are demonstrated.     

Human-like natural behavior generation based on involuntary motions for humanoid robots

Human behaviors consist of both voluntary and involuntary motions. Almost all behaviors of task-oriented robots, however, consist solely of voluntary motions. Involuntary motions are important for generating natural motions like those of humans. Thus, we propose a natural behavior generation method for humanoid robots that is a hybrid generation between voluntary and involuntary motions. The key idea of our method is to control robots with a hybrid controller that combines the functions of a communication behavior controller and body balancing controllers. We also develop a wheeled inverted pendulum type of humanoid robot, named “Robovie-III”, in order to generate involuntary motions like oscillation. By applying our method to this robot and conducting preliminary experiments, we verify its validity. Experimental results show that the robot generates both voluntary and involuntary motions.     

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.     

Analysis of Humanoid Appearances in Human–Robot Interaction

Identifying the extent to which the appearance of a humanoid robot affects human behavior toward it is important. We compared participant impressions of and behaviors toward two real humanoid robots in simple human-robot interactions. These two robots, which have different appearances but are controlled to perform the same recorded utterances and motions, are adjusted by a motion-capturing system. We conducted an experiment with 48 human participants who individually interacted with the two robots and also with a human for reference. The results revealed that different appearances did not affect participant verbal behaviors, but they did affect such nonverbal behaviors as distance and delay of response. These differences are explained by two factors: impressions and attributions.     

Potential field method to navigate several mobile robots

Navigation of mobile robots remains one of the most challenging functions to carry out. Potential Field Method (PFM) is rapidly gaining popularity in navigation and obstacle avoidance applications for mobile robots because of its elegance. Here a modified potential field method for robots navigation has been described. The developed potential field function takes care of both obstacles and targets. The final aim of the robots is to reach some pre-defined targets. The new potential function can configure a free space, which is free from any local minima irrespective of number of repulsive nodes (obstacles) in the configured space. There is a unique global minimum for an attractive node (target) whose region of attraction extends over the whole free space. Simulation results show that the proposed potential field method is suitable for navigation of several mobile robots in complex and unknown environments. Saroj Kumar Pradhan is faculty of Mechanical Engineering Department with N.I.T., Hamirpur, HP, India. He has received his B.E. degree in Mechanical Engineering from Utkal University and M.E. in Machine Design and Analysis from NIT Rourkela. He has published more than 17 technical papers in international journals and conference proceedings. His areas of research include mobile robots navigation and vibration of multilayred beams. Dayal R. Parhi is working as Assistant Professor at NIT Rourkela, India. He has obtained his first Ph.D. degree in “Mobile Robotics” from United Kingdom and Second Ph.D. in “Mechanical Vibration” from India. He has visited CMU, USA as a “Visiting Scientist” in the field of “Mobile Robotics”. His main areas of current research are “Robotics” and “Mechanical Vibration”. He is supervising five Ph.D. students in the fields of Robotics and Vibration. Email: dayalparhi@yahoo.com. Anup Kumar Panda Received his M.Tech degree from IIT, Kharagpur in 1993 and Ph.D. degree from Utkal University in 2001. He is currently an assistant professor in the Department of Electrical Engineering at National Institute of Technology, Rourkela, India. His areas of research include robotics, Machine Drives, harmonics and power quality. He has published more than 30 technical papers in journals and conference proceedings. He is now involved in two R&D projects funded by Government of India. R. K. Behera is a Senior Lecturer of Mechanical Engineering at National Institute of Technology, Rourkela, India. He has been working as lecturer for more than 10 years. He obtained his BE degree from IGIT, Sarang, of Utkal University. He obtained his ME and Ph.D degrees, both in the field of mechanical engineering from NIT Rourkela.     

基于分层Option的仿人机器人相似性关键姿势转换

针对运动捕获系统获取的人体运动轨迹固定、难以实现仿人机器人关键姿势转换问题,提出了一种基于分层Option学习的仿人机器人关键姿势相似性转换方法。构建多级关键姿势树状结构,从关节相似差异、时刻整体相似差异、周期整体相似差异等角度描述了关键姿势差异,引入分层强化Option学习方法,建立关键姿势与Option行为集,由关键姿势差异的累计奖励将SMDP-Q方法逼近最优Option值函数,实现了关键姿势的转换。实验验证了方法的有效性。     

仿人机器人足迹规划建模及算法实现

足迹规划是仿人机器人运动规划领域的一个新思想.本文建立了仿人机器人足迹规划的模型,并通过构建启发式成本函数,利用A*算法予以实现.针对复杂多障碍物环境,特别提出了基于可变落地足迹数量的复合足迹转换模型的方法.仿真实验证明了规划模型和算法的有效性和完备性,规划效果达到仿人机器人在线运动规划的要求.同时,数值实验也证明了在复杂多障碍物环境下复合足迹转换模型的必要性和优越性.     

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.     

Stabilisation times after transitions to standing from different working postures

Transitioning to standing after maintaining working postures may result in imbalance and could elicit a fall. The objective of this study was to quantify the magnitude of imbalance using a stabilisation time metric. Forty-five male participants completed three replications of conditions created by one of four working postures (bent at waist, squat, forward kneel, reclined kneel) and three durations within posture. Participants transitioned to quiet standing at a self-selected pace. Stabilisation time, based on changes in centre of pressure velocity, was used to indicate the initiation of steady state while standing. Stabilisation time was significantly affected by static postures but not duration within posture. The largest stabilisation times resulted from transitions initiated from a bent at waist posture. The smallest were associated with the kneeling postures, which were not significantly different from each other. Findings may lead to recommendations for redesign of tasks, particularly in high-risk environments such as construction.

Statement of Relevance: Task performance on the jobsite often requires individuals to maintain non-erect postures. This study suggests that working posture affects stabilisation during transition to a standing position. Bending at the waist and squatting resulted in longer stabilisation times, whereas both kneeling postures evaluated resulted in greater imbalance but for a shorter duration.     

Matters of (Meta-) Modeling

With the recent trend to model driven engineering a common understanding of basic notions such as “model” and “metamodel” becomes a pivotal issue. Even though these notions have been in widespread use for quite a while, there is still little consensus about when exactly it is appropriate to use them. The aim of this article is to start establishing a consensus about generally acceptable terminology. Its main contributions are the distinction between two fundamentally different kinds of model roles, i.e. “token model” versus “type model” (The terms “type” and “token” have been introduced by C.S. Peirce, 1839–1914.), a formal notion of “metaness”, and the consideration of “generalization” as yet another basic relationship between models. In particular, the recognition of the fundamental difference between the above mentioned two kinds of model roles is crucial in order to enable communication among the model driven engineering community that is free of both unnoticed misunderstandings and unnecessary disagreement.     

Static and dynamic lifting strength at different reach distances in symmetrica] and asymmetrical planes

Postural and therefore biomechanical standardization in strength testing has not been rigorously and consistently applied. To develop a quantitative relationship between strength and posture (body position, symmetry, and reach) 30 normal subjects (18 male and 12 females) were required to stoop and squat lift or exert in the relevant posture against a standardized instrumented handle. The isometric lifting efforts and isokinetic lifts were studied. The isokinetic lifts were done at a linear velocity of 50cm/s of the hand displacement from the floor to the knuckle heights of the respective subjects in stoop and squat postures. The isometric stoop lifting efforts were exerted in two standardized postures: (a) with 60° hip flexion; and (b) with 90° hip flexion. The isometric squat lifting efforts were also exerted in two standardized postures: (a) with 90° knee flexion; and (b) with 135° knee flexion. All isometric lifting efforts and isokinetic lifts were performed at half, three-quarters, and full horizontal reach in sagitally symmetrical, 30° left lateral, and 60° left lateral planes. Isometric stoop and squat lifting efforts were also measured in self-selected optimal postures. These 56 conditions were tested in random order. The analysis of variance revealed that the gender, the mode of lifting, the postural asymmetry and reach of lifting affected the strength significantly (p<0·0001). Most two-way and three-way interactions were significant (p<0·01). Of 108 prediction regression equations, 103 were significant with up to 90% of the variation explained by anthropometric variables and sagittal plane strength. The reach affected the strength most profoundly followed by postural asymmetry and the mode of lifting.     

Humanoid odometric localization integrating kinematic,inertial and visual information

We present a method for odometric localization of humanoid robots using standard sensing equipment, i.e., a monocular camera, an inertial measurement unit (IMU), joint encoders and foot pressure sensors. Data from all these sources are integrated using the prediction-correction paradigm of the Extended Kalman Filter. Position and orientation of the torso, defined as the representative body of the robot, are predicted through kinematic computations based on joint encoder readings; an asynchronous mechanism triggered by the pressure sensors is used to update the placement of the support foot. The correction step of the filter uses as measurements the torso orientation, provided by the IMU, and the head pose, reconstructed by a VSLAM algorithm. The proposed method is validated on the humanoid NAO through two sets of experiments: open-loop motions aimed at assessing the accuracy of localization with respect to a ground truth, and closed-loop motions where the humanoid pose estimates are used in real-time as feedback signals for trajectory control.