Humanoid Robots - New Developments Part 15 ppsx

482 Humanoid Robots, New Developments the deviation of the body’s center-of-mass. G1 is the transfer function of PID controller, and G2 is the transfer function of inverted pendulum model. The results showed that the gain of the PID parameter D K is decreased significantly in eyes closed (131.5±37.6Nms/rad in eyes open and 90.4±26.0Nms/rad in eyes closed᧨p<0.001, Fig.14), however, P K and I K are unchanged. Simulation results also proved that when decreasing the gain of D K locus of simulated is more like the measured spontaneous body sway in eyes closed. The results suggested environmental visual cue is important for balance-keeping control, and this effect is pattern-dependent. Of cause, angular velocity is also increased when eyes are closed (Fig.15). Fig.14. Averaged D K values of the 10-subject decreased from A to D. No significant differences was found between A and B, however, others showed significant difference. **: p < 0.01. Balance-Keeping Control of Upright Standing in Biped Human Beings and its Application for Stability Assessment 483 There are two hypothesizes have been proposed about the mechanism of the visual effect on balance-keeping. One regards that information coming from proprioception of extra-ocular muscles is important for balance-keeping control [34] . The other theory is “retinal slip” insisted that images slip on the retinal is used as a cue for balance-keeping control [35] . Our present studies agreed with the retinal slip hypothesis. Fig.15. Averaged values of the TSS in different visual stimulations are increased from A to D. However, no significant difference between A and B. ***: p < 0.001. 9. Summary Upright standing is a simple and basic posture of human beings. However, the relatively large mass of the upper body and its elevated position in relation to the area of support during standing accentuate the importance of an accurate control of trunk movements for the maintenance of equilibrium. The kinematics and control strategy of the central nervous system have been studied in recent decade, which brought a PID control algorithm to model the balance-keeping in upright standing and had successfully interpreted the phenomenon of spontaneously body sway. Modeling the human body as two-link inverted pendulum system, we successfully identified parameters of individual’s PID parameters and make this model analyzable and practicable. The simulation results, both of the body sway and the spectral response, are quite consistent with experimental data. This proved that the PID 484 Humanoid Robots, New Developments model is a reasonable and a useful method as well as by measuring the averaged angular velocity. Both of the two methods help for falls prediction, and become a promising method for falls prevention. Many authors have argued that complex architectures including feedforward/feedback is necessary for the maintenance of upright stance, however, our studies together with some other recent studies have shown that a model based primarily on a simple feedback mechanism with 120-ms to 150-ms time delay can account for postural control during a broad variety of disturbance [36] . Also, one interesting result is that D k is a key parameter related to individual balance keeping ability. Since D k is not just influenced by visual cue but also sensitive to aging. It seems that human balance keeping ability is mainly determined by the gains regulation of D k , and still there have much works to be done in the future. 10. References 1) William, M. and Lissner, H.R. Boimechanics of human motion. W.B. Saunder Company, Philadephia, 1977. 2) Whitney, R.J. The strength of the lifting action in man. Ergonomics 1, 101-128, 1958. 3) Magnus, R. Korperstellung. Berlin: Sprinter, 1924. 4) De Kleijn, A., Experimental physiology of the labyrinth. J Laryngol. & Otol., 38, 646-663, 1923. 5) Redfern, M.S., Yardley, L. and Bronstein, A.M Visual influence on balance, J Anxiety Disord., 15, 81-94, 2001. 6) Fitzpatrick, R.C. and Day, B.L Probing the human vestibular system with galvanic stimulation. J Appl Physiol., 96, 2301-2306, 2004. 7) Maurer, C. and Peterka, R. J Multisensory control of human upright stance. Exp Brain Res., 171, 231-250, 2005. 8) Geurts, A.C. Haart, M. van Nes I.J. and Duysens, J A review of standing balance recovery from stroke. Gait Posture, 22, 267-281, 2004. 9) Morosso, P.G. and Schieppati, M Can muscle stiffness alone stabilize upright standing? J Neurophysiol. 82, 1622-1226, 1999. 10) Bloem, B.R., Van Dijk, J.G., and Beckley, D.J., et al. Altered postural reflexes in Parkinson's disease: a reverse hypothesis. Med Hypotheses 39, 243-247, 1992. 11) Ji, Z., Findley, T., Chaudhry H. and Bukiet, B Computational method to evaluate ankle postural stiffness with ground reaction forces. J Rehabil Res Dev. 41, 207-214, 2004. 12) Jiang, Y., Nagasaki, S. and Kimura, H The Relation Between Trunk Sway and the Motion of Centre of Pressure During Quiet Stance. Jpn. J. Phys. Fit. Sport Med., 52, 533-542, 2003. 13) Jiang, Y., Nagasaki, S., Matsuura Y. and Zhou, J Dynamic studies on human body sway by using a simple model with special concerns on the pelvic and muscle Roles. Asian J. Control, 8, 297-306, 2006. 14) Massion, J., Postural Control Systems in Developmental Perspective. Neurosci. Biobehav. Rev., 22, 465-472, 1998. 15) Krishnamoorthy, V., Latash, M.L., Scholz, J.P. and Zatsiorsky, V.M Muscle Synergies During Shifts of the Center of Pressure by Standing Persons. Exp. Brain Res., 152, 281-292, 2003. Balance-Keeping Control of Upright Standing in Biped Human Beings and its Application for Stability Assessment 485 16) Jiang, Y., Nagasaki, S. and Matsuura Y. et al The role of ankle joint in the control of postural stability during upright standing on one-foot. Jpn. J Educ. Health. Sci.,49, 277-284, 2004. 17) Cote K. P., Brunet M. E., Gansneder B.M. and Shultz S.J Effects of Pronated and Supinated Foot Postures on Static and Dynamic Postural Stability. J Athl Train. 40, 41-46, 2005. 18) Masani K., Vette A.H., Popovic M.R Controlling balance during quiet standing: proportional and derivative controller generates preceding motor command to body sway position observed in experiments. Gait Posture. 23, 164-172, 2006. 19) Mergner T., Maurer C. and Peterka R.J A multisensory posture control model of human upright stance. Prog. Brain Res. 142, 189-201, 2003. 20) Dickin D.C., Brown L.A. and Doan J.B Age-dependent differences in the time course of postural control during sensory perturbations. Aging Clin. Exp. Res. 18, 94-99, 2006. 21) Imaoka K., Murase H. and Fukuhara M., Collection of data for healthy subjects in stabilometry. Equilibrium Res. Suppl., 12, 1-84, 1997. 22) Chaudhry H., Findley T., Quigley K.S. et al Postural stability index is a more valid measure of stability than equilibrium score. J Rehabil. Res. Dev. 42, 547-556, 2005. 23) Tinetti M.E., Williams T. F. and Mayewski R., Fall risk index for elderly patients based on number of chronic disabilities. Am. J. Med., 80, 429-434, 1986. 24) Paper S.A. and Soames R. W The influence of stationary auditory fields on postural sway behaviour in man. Eur. J. Appl. Physiol. Occup. Physiol., 63, 363-367, 1991. 25) Horstmann G. A and Dietz V A basic posture control mechanism: the stabilization of the centre of gravity. Electroencephalogr. Clin. Neurophysiol., 76, 165-176, 1990. 26) Berger W., Trippel M., Discher M. and Dietz V., Influence of subjects’ height on the stabilization of posture. Acta Otolaryngol., 112, 22-30, 1992. 27) Kimura M., Okuno T., Okayama Y. and Tanaka Y Characteristics of the ability of the elderly to maintain posture. Rep. Res. Cent. Phys. Ed., 26, 103-114, 1998. 28) Giese M.A., Dijkstra T.M., Schoner G. and Gielen C.C Identification of the nonlinear state-space dynamics of the action-perception cycle for visually induced postural sway. Biol. Cybern. 74, 427-437, 1996. 29) Jeka J., Oie K., Schoner G., Dijkstra T. and Henson E Position and velocith coupling of postural sway to somatosensory drive. J Neurophysiol. 79, 1661-1674, 1988. 30) Jiang, Y., Nagasaki, S., Matsuura Y. et al Postural sway depends on aging and physique during upright standing in normals. Jpn. J Educ. Health. Sci.,48, 233-238, 2002. 31) Kimura Hidenori, Yifa Jiang, A PID model of human balance keeping. IEEE Control System Magazine, 26(6), 18-23, 2006. 32) Nagasaki, Jiang, Y., S., Yoshinori F. et al Falls risk prediction in old women: evaluated by trunk sway tests in static upright stance. Jpn. J Educ. Health. Sci.,48, 353-358, 2003. 486 Humanoid Robots, New Developments 33) Qin S., Nagasaki S., Jiang Y., et al. Body sway control and visual influence during quiet upright standing. Jpn. J Physic. Fitness & Sports Medicine, 55, 469-476, 2006. 34) Baron J.B., Ushio N. and Tangapregassom M.J Orthostatic postural activity disorders recorded by statokinesimeter in post-concussional syndromes: oculomoter aspect.Clin. Otolaryngol. Allied Sci., 4,169-174. 1979. 35) Glasauer S., Schneider E., Jahn K., Strupp M., and Brandt T. How the eyes move the body. Neurology. 65, 1291-1293, 2005. 36) Maurer C. and Peterka R.J A new interpretation of spontaneous sway measures based on a simple model of human postural control. J Neurophysiol., 93, 189- 200,2005. 27 Experiments on Embodied Cognition: A Bio-Inspired Approach for Robust Biped Locomotion Frank Kirchner, Sebastian Bartsch and José DeGea German Research Center for Artificial Intelligence, And University of Bremen, Robotics Lab, Bremen Germany 1. Introduction Recently, the psychological point of view that grants the body a more significant role in cognition has also gained attention in artificial intelligence. Proponents of this approach would claim that instead of a ‘mind that works on abstract problems’ we have to deal with and understand ‘a body that needs a mind to make it function’ (Wilson, 2002). These ideas differ quite radically from the traditional approach that describes a cognitive process as an abstract information processing task where the real physical connections to the outside world are of only sub-critical importance, sometimes discarded as mere ‘informational encapsulated plug-ins’ (Fodor, 1983). Thus most theories in cognitive psychology have tried to describe the process of human thinking in terms of propositional knowledge. At the same time, artificial intelligence research has been dominated by methods of abstract symbolic processing, even if researchers often used robotic systems to implement them (Nilsson, 1984). Ignoring sensor-motor influences on cognitive ability is in sharp contrast to research by William James (James, 1890) and others (see (Prinz, 1987) for a review) that describe theories of cognition based on motor acts, or a theory of cognitive function emerging from seminal research on sensor-motor abilities by Jean Piaget (Wilson, 2002) and the theory of affordances by (Gibson, 1977). In the 1980s the linguist Lakoff and the philosopher Johnson (Lakoff & Johnson, 1980) put forward the idea of abstract concepts based on metaphors for bodily, physical concepts; around the same time, Brooks (Brooks, 1986) made a major impact on artificial intelligence research by his concepts of behavior based robotics and interaction with the environment without internal representation instead of the sense- reason-act cycle. This approach has gained wide attention ever since and there appears to be a growing sense of commitment to the idea that cognitive ability in a system (natural or artificial) has to be studied in the context of its relation to a ‘kinematically competent’ physical body. Among the most competent (in a multi functional sense) physical bodies around are certainly humans, so the study of humanoid robots appears to be a promising field for 488 Humanoid Robots, New Developments understanding the mechanisms and processes involved in generating intelligence in technical systems. In the following we will give an overview of the field of humanoid robot research. 2. State of the Art Humanoids A review on humanoid robot systems, cannot be made without bearing in mind that many of the current developments concentrate on one or the other feature of human performance. Some of them are good at manipulating objects with anthropomorphic arms but move over a wheeled platform. Some others walk on two legs but lack of a torso and arms. Some combine those two features but lack a human appearance or communication abilities. Some other developments concentrate on human-like communication skills, like speech recognition, gestures and the generation of facial expressions that denote sadness, happiness, fear or any other state that a human is able to recognise. All these aspects are crucial for the final goal of attaining a robot that is perceived as humanoid. A robot that transmits its feelings, ideas or thoughts, that behaves like a human when performing a task or a movement and with which a human feels safe and confident to collaborate with are key points for the social acceptance of a humanoid robots. A description of the state of the art might start chronologically since the development of the first complete humanoid, the Wabot-1 from the Waseda University in 1970 but we choose to list the developments on the humanoid field beginning with the systems that incorporate the more human-like features and are considered the most advanced systems to continue describing systems that work on single or a combination of several human-like aspects, all of them of major interest and importance. Before describing the most important developments on the field, it is worth mentioning a few aspects about observable facts depending on the origin of the robot: namely, Asia, Europe or USA. There are differences on the complexity of the systems but also on the different approaches that are followed or the motivations that lead the development of the robot. Japan (and Korea in a minor extent) are seen as world leaders in the humanoid robot research. They have the most complex robots with the most similar human resemblance. They believe in a complete immersion of the robots in a future society, where robots do not differentiate easily from humans. The more remarkable points of their developments are the hardware (the mechanics), the physical appearance of the robot and the fact that the industry is leading the research on these robots, expecting a huge market in a near future. USA entered the humanoid era because of the needs posed by the claims of the ‘modern’ Artificial Intelligence: the need for a human-like body as a prerequisite for a robot to achieve human-like intelligence. It is the interaction with the environment and the gathered experience what is thought to be the basis for the appearance of intelligent behaviors. Europe, on the other side, is basically concerned with giving a real application to the development of humanoid robots and that is on the service robotics area, for rehabilitation and/or personal care of the elderly. The most advanced systems are heading towards that goal. At the same time, inspiration from biological systems is a very common term to describe the approaches used in those robots. Several European projects work on sensorimotor coordination, cognitive architectures and learning approaches that have their roots in the cooperation with scientists in the neuroscience, biology and psychology areas. The ASIMO robot from Honda (Hirai, 1998) (cf. figure 1) is without a doubt the most advanced humanoid robot nowadays. Honda employed vast human and economical Experiments on Embodied Cognition: A Bio-Inspired Approach for Robust Biped Locomotion 489 resources to achieve a complete human-like looking robot, pushing forward the research in many areas. The current research model is 130cm tall, weights 54 kg and is able to run at 6km/h (December 2005). The research began in 1986, achieving a first ASIMO prototype in the year 2000. Nowadays, ASIMO is the only robot that is able to autonomously walk around and climb stairs and slopes. Furthermore, it is able to understand some human gestures and interact with people using its speech recognition system and some pre- programmed messages. ASIMO can also push a cart, keeping a fixed distance to it while moving and still maintaining the capability to change direction or speed of movement, walking hand-in-hand with a person or carrying a tray. Fig. 1. Honda ASIMO (left picture), Sony QRIO (middle picture), and ROBONAUT (right picture). The HRP-2P (Kaneko, 2003) robot specified by AIST (National Institute of Advanced Industrial Science and Technology, Japan) and whose hardware was manufactured by the Kawada Industries (a company that also worked with Honda and the University of Tokyo in the development of the ASIMO and the H6-H7 robots) is one of the most advanced humanoids nowadays. It differs from ASIMO on the fact that it is a research prototype whose software is open to any roboticist. Moreover, it was designed to walk on uneven terrains and recover from falling positions, features not yet possible for ASIMO. It weights 58kg and is 154cm tall. Probably the third robot in importance in Japan is the H7 (Kagami, 2001) from the University of Tokyo. However, there is not much information available apart from videos showing its capabilities walking on a flat terrain. As above mentioned, Kawada Inc. was responsible for the hardware development. It weights 55kg, is 147cm tall and has 30 DoF. Sony entered the humanoid world in 1997 with the SDR-1X series, achieving the SDR-4X version in 2003, named QRIO (Ischida, 2003) (cf. Fig. 1) as was intended to be commercially available. In 2006 Sony announced the decision to stop the further development of the robot. QRIO is comparable to ASIMO in its walking capabilities although since it was designed as an entertainment robot, its size is substantially smaller than ASIMO: its weights 7kg and is 58cm tall. Its main features include the ability to adapt its walking to the most difficult situations: from walking on irregular or tiled terrains to react to shocks and possible falling 490 Humanoid Robots, New Developments conditions. But since its origins as entertainment robot, the most remarkable features are those that enhanced its interaction capabilities with people: the robot is able to recognise faces, use memory to remember a previously seen person or his/her words, detect the person who is speaking and incorporates a vocabulary of more than 20,000 words that enables the robot to maintain simple dialogues with humans. Fig. 2. The Robot BIN-HUR based on Kondo’s KHR-1. Hubo (Il Woo, 2005) is the most well-known humanoid robot in South Korea and one of the world's most advanced. It is the latest development of the series of KHR robots (KHR-1, KHR-2 and KHR-3 – Hubo). It is 125cm tall and weights 56kg, having 41 DoF. Apart from improving in this latest version its walking abilities, Hubo is now also able to talk to someone by using a speech recognition system. Fujitsu also entered the humanoid area in 2003 with the HOAP-1 (Murase, 2001). Its major claim with it was its learning capabilities and the use of neural networks to control the locomotion implementing a Central Pattern Generator (CPG), proven to be one of the responsible neural circuitry for the locomotion on vertebrates. These artificial neural Experiments on Embodied Cognition: A Bio-Inspired Approach for Robust Biped Locomotion 491 oscillators are used to create rhythmic motions to generate the appropriate gait. The major advantage is claimed to be its adaptation to the environment and new terrain configurations and the minimum computational effort to control the locomotion. No need for modelling kinematics, dynamics or generating stable trajectories using complex criteria are required. It was intended to be used in research labs and universities as an educational tool where to test different algorithms and for that reason provides an open source software and weights only 6kg and is 48cm tall. It can walk up to 2km/h and is sold at about 50,000€. In 2004, HOAP-2 received the Technical Innovation Award from the Robotics Society of Japan. Toyota also presented a series of partner robots (2005), one of them walking in two legs, finding its application in the elderly care and rehabilitation. As a curious feature, Toyota included artificial lips with human finesse what, together with their hands, enables them to play trumpets in a similar way a human does. WABIAN-RIII and WENDY (Ogura, 2004) are the latest developments from the Waseda University, as already mentioned, the pioneers in the humanoid field with the first full-scale humanoid robot, a project that began in 1970 and finished three years later with Wabot-1. WABIAN-RII continues the research in dynamical walking plus load carrying and the addition of emotional gesture while performing tasks. Likewise, WENDY incorporates emotional gestures to the manipulation task that is being carried out. WABIAN-RII weights 130kg and is 188cm tall while WENDY is 150cm tall and weights 170kg. Johnnie (Löffler, 2000) is probably the most well-known and advanced humanoid robot in Europe. It was developed at the University of Munich with the aim of realising a human- like walking, in this case based on the well-established Zero Moment Point (ZMP) approach introduced by Honda in the ASIMO robot, but with the aid of a vision system. It is able to walk on different terrains and climb over some stairs. It is 180cm tall and weights 45kg. Robonaut (Ambrose, 2001) (cf. figure 1) is a humanoid robot developed by the NASA with the aim of replacing a human astronaut in EVA tasks (outside the vehicle). The main feature of the robot is a human dexterous manipulation capability that enables it to perform the same tasks an astronaut would perform and with the same dexterity. The robot is not autonomous but tele-operated from inside the vehicle. Since legs have no utility in space, the robot is composed of two arms and a torso that is attached to a mechanical link enabling the positioning of the robot in any required position/orientation. Because of the bulky suits the astronauts have to wear to protect against radiations, their manipulation capabilities are greatly reduced and the handles, tools and interfaces they use are designed to be handled with their special gloves. A robot, even though needing some protection against radiation, would not required such a bulky suit thus recovering to a certain extent a human dexterity. Moreover, risks for astronauts are avoided on these missions outside the spatial vehicle. It has the size of a human torso and arm, with 54 DoF in total: 14 for each hand, 7 for each arm and the link to the vehicle, 2 in the neck and 3 on the waist. In the field of human-robot interaction, the robot Cog (Brooks, 1998), from the MIT AI Lab, is the best example. Cog is composed of a torso, two arms and a head. The main focus of this project is to create a platform in order to prove the ideas exposed by Rodney Brooks claiming that human-like intelligence appearance requires a human-like body that interacts with the world in the same way a human does. Besides, for a robot to gain experience in interacting with people it needs to interact with them in the same way people do. One underlying hope in Brooks theory is that: Having a human-like [...]... Honda Humanoid Robot” In Proc of the 1998 IEEE Int Conf on Robotics & Automation, p.132 1-1 326 (1998) Ishida, T “A small biped entertainment robot SDR-4X II” In Proceedings of the 2003 IEEE Internation Symposium on Computational Intelligence in Robotics and Automation, pp 104 6-1 051, vol.3, 2003 II-Woo Park "Mechanical Design of Humanoid Robot platfrom KHR-3(KAIST Humanoid Robot-3: HUBO)", in Humanoids... Point Relations • Because each body part is processed separately, each joint model has to be added twice, once to each associated body part 512 Humanoid Robots, New Developments • The generated point pairs each represent one point on the model and the associated artificial data point So each pair has to be added to one body part as Model - Data and to the other Data - Model relation to retrieve the desired... behavior 502 Humanoid Robots, New Developments Fig 12 Desired and real angle (degree) from left arm and leg joints over 4000 ms as an average over 5 recurrences Fig 13 Tilt values for rear-front and right-left pitch as an average over 5 recurrences Experiments on Embodied Cognition: A Bio-Inspired Approach for Robust Biped Locomotion 503 Fig 14 Calculated error from the balance behavior’s PID-controller... of Adaptive Behavior, workshop on Socially Situated Intelligence, Zurich Switzerland 2 5-4 0 Brooks, R et al “The Cog Project: Building a Humanoid Robot” In Computation for Metaphors, Analogy and Agents, Vol 156 2 of Springer Lecture Notes in Artificial Intelligence, Springer-Verlag, 1998 504 Humanoid Robots, New Developments Brooks, R A (1986) A robust layered control system for a mobile robot IEEE... example images from a sequence of 15 seconds containing a “bow” and a “wave” movement The first row shows the scene image, which has been also used for segmentation of face and hands The second and third row contain the tracking result 516 Humanoid Robots, New Developments with 3d data only (row 2) and 2d data only (row 3), where the 3d data has been acquired with the Time-of-Flight camera and the 2d data... ) = 1 N 2 N R( x ' i ) − p ' i +t ' (2) i =1 This leads to 1 f ( R, t ) = N 2 N R( x 'i ) − p'i i =1 N − 2t i =1 (R( xi ' ) − pi ') + N t ' 2 (3) 508 Humanoid Robots, New Developments In equation (3), the first part is independent from t ' , the second part reveals to zero Therefore the function becomes minimal if t ' = 0 Transformation yields t = μ p − R( μ x ) (4) Having the optimal translation (giving... modelled easily as artificial correspondences and will thus be considered automatically in each computation step 510 Humanoid Robots, New Developments For each junction of model parts, a set of elastic bands is defined (see Fig 3) These relations set up corresponding points on both model parts The corresponding points can then be used within the model fitting process to adjust the model configuration... designed as a PID-Controller takes the tilt value shown in figure 7 as input for the controller and writes the controller’s output values multiplied with a specific factor for each joint to the servos Negative sensor values represent a right or rather rear leaning, and positive values a left and accordingly front leaning 498 Humanoid Robots, New Developments As you can see, the output of the PID-Controller... assigned to a single body part may also be generated by a stereo vision system tracking special body parts like the face or the hands 3d point-to-point relations are 3d points that can be assigned to a given point on the tracked human body Thus, tracking of special features or points (e.g with markers, or magnetic field trackers attached to the human body) can be integrated 2d point-to-line relations can... is weighted with a measure that describes its accuracy The ICP algorithm then incorporates these weights in the model-fitting step Thus it is possible to weight a 2d face tracker much higher than a single 3d point from a Time-of-Flight camera, or to weight 3d points from a Time-of-Flight-camera slightly higher than points from the stereo reconstruction due to the measuring principle and the sensor accuracy . 482 Humanoid Robots, New Developments the deviation of the body’s center-of-mass. G1 is the transfer function of PID controller, and G2. physical bodies around are certainly humans, so the study of humanoid robots appears to be a promising field for 488 Humanoid Robots, New Developments understanding the mechanisms and processes. trunk sway tests in static upright stance. Jpn. J Educ. Health. Sci.,48, 35 3-3 58, 2003. 486 Humanoid Robots, New Developments 33) Qin S., Nagasaki S., Jiang Y., et al. Body sway control and