Abstract
In the previous chapter, it was highlighted that human-like motion will be beneficial for the integration humanoid robots into real-world scenarios. This chapter focuses on human motion, in particular, reaching motion, which is the general goal of the control approaches pursued in this book. Such motion is largely consistent across the healthy population, in a large part, due to the structural constraints of human physiology. In this chapter, we review literature related to the understanding of human motion and the handling of redundancies, which are of particular interest in robotic arm control. A variety of approaches to understanding such motion will be considered in addition to methods of recording human motion and scaling that motion to artificial agents, which typically lack the full complexity of the human body.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Abend W, Bizzi E, Morasso P (1982) Human arm trajectory formation. Brain: J Neurol 105(Pt 2):331
Adams B (2001) Learning humanoid arm gestures. In: Working notes – AAAI spring symposium series: learning grounded representations, Stanford
Alexander R (1997) A minimum energy cost hypothesis for human arm trajectories. Biol Cybern 76(2):97–105
Argall B, Chernova S, Veloso M, Browning B (2009) A survey of robot learning from demonstration. Robot Auton Syst 57(5):469–483
Ascenion (2015) Trakstar @ONLINE. http://www.ascension-tech.com/products/. Accessed 05 Sept 15
Atkeson C (1989) Learning arm kinematics and dynamics. Ann Rev Neurosci 12(1):157–183
Atkeson C, Hollerbach J (1985) Kinematic features of unrestrained vertical arm movements. J Neurosci 5(9):2318
Atkeson C, Schaal S (1997) Robot learning from demonstration. In: 14th international conference on machine learning, Nashville, Citeseer, pp 12–20
Bonnechere B, Jansen B, Salvia P, Bouzahouene H, Omelina L, Moiseev F, Sholukha V, Cornelis J, Rooze M, Jan SVS (2014) Validity and reliability of the kinect within functional assessment activities: comparison with standard stereophotogrammetry. Gait Posture 39(1):593–598
Bray J (2015) Markerless based human motion capture: a survey @ONLINE. http://visicast.co.uk/members/move/Partners/Papers/MarkerlessSurvey.pdf
Bremner P, Leonards U (2015) Speech and gesture emphasis effects for robotic and human communicators: a direct comparison. In: Proceedings of the tenth annual ACM/IEEE international conference on human-robot interaction (HRI ‘15), pp 255–262. doi:10.1145/2696454.2696496
Bullock D, Grossberg S (1988) Neural dynamics of planned arm movements: emergent invariants and speed-accuracy properties during trajectory formation. Psychol Rev 95(1):49–90
Burdet E, Milner T (1998) Quantisation of human motions and learning of accurate movements. Biol Cybern 78(4):307–318
Burdet E, Tee K, Mareels I, Milner T, Chew C, Franklin D, Osu R, Kawato M (2006) Stability and motor adaptation in human arm movements. Biol Cybern 94(1):20–32
Ciocarlie M, Clanton S, Spalding M, Allen P (2008) Biomimetic grasp planning for cortical control of a robotic hand. 2008 IEEE/RSJ international conference on intelligent robots and systems, Nice, pp 2271–2276
Clark RA, Bower KJ, Mentiplay BF, Paterson K, Pua YH (2013) Concurrent validity of the microsoft kinect for assessment of spatiotemporal gait variables. J Biomech 46(15):2722–2725
Cruse H (1986) Constraints for joint angle control of the human arm. Biol Cybern 54(2):125–132
Cruse H, Brüwer M (1987) The human arm as a redundant manipulator: the control of path and joint angles. Biol Cybern 57(1):137–144
De Sapio V, Warren J, Khatib O, Delp S (2005) Simulating the task-level control of human motion: a methodology and framework for implementation. V Comput 21(5):289–302
De Sapio V, Warren J, Khatib O (2006) Predicting reaching postures using a kinematically constrained shoulder model. Adv Robot Kinemat 3:209–218
Delp S, Loan J (2000) A computational framework for simulating and analyzing human and animal movement. Comput Sci Eng 2(5):46–55. doi:10.1109/5992.877394
Delp S, Anderson F, Arnold A, Loan P, Habib A, John C, Guendelman E, Thelen D (2007) OpenSim: open-source software to create and analyze dynamic simulations of movement. IEEE Trans Biomed Eng 54(11):1940–1950
Demircan E, Sentis L, De Sapio V, Khatib O (2008) Human motion reconstruction by direct control of marker trajectories. In: Lenarcic J, Wenger P (eds) Advances in robot kinematics: analysis and design, Springer, Netherlands, pp 263–272
Demiris Y, Dearden A (2005) From motor babbling to hierarchical learning by imitation: a robot developmental pathway. In: Berthouze L, Kaplan F, Kozima H, Yano H, Konczak J, Metta G, Nadel J, Sandini G, Stojanov G, Balkenius C (eds) Proceedings of the fifth international workshop on epigenetic robotics: modeling cognitive development in robotic systems, Nara, vol 123. Lund University Cognitive Studies. ISBN:91-974741-4-2
Desmurget M, Jordan M, Prablanc C, Jeannerod M (1997) Constrained and unconstrained movements involve different control strategies. J Neurophysiol 77(3):1644
Feldman A (1974) Change of muscle length due to shift of the equilibrium point of the muscle-load system. Biofizika 19:534–538
Fitts P, Peterson J (1964) Information capacity of discrete motor responses. J Exp Psychol 67(2):103–112
Flash T, Hogan N (1985) The co-ordination of arm movements: An experimentally confirmed mathematical model. J Neurosci 5(7):1688–1703
Fougner A, Scheme E, Chan AC, Englehart K, Stavdahl Ø (2011) Resolving the limb position effect in myoelectric pattern recognition. IEEE Trans Neural Syst Rehabil Eng 19(6):644–651
Fung Y (1993) Biomechanics: mechanical properties of living tissue. Springer, New York
Gams A, Ude A (2009) Generalization of example movements with dynamic systems. In: Humanoids 2009. 9th IEEE-RAS international conference on humanoid robots, pp 28–33. doi:10.1109/ICHR.2009.5379607
Gams A, Van den Kieboom J, Dzeladini F, Ude A, Ijspeert AJ (2015) Real-time full body motion imitation on the coman humanoid robot. Robotica 33(05):1049–1061
Georgopoulos A, Kalaska J, Massey J (1981) Spatial trajectories and reaction times of aimed movements: effects of practice, uncertainty, and change in target location. J Neurophysiol 46(4):725
Grebenstein M, van der Smagt P (2008) Antagonism for a highly anthropomorphic hand-arm system. Adv Robot 22(1):39–55
Hall S (2003) Basic biomechanics, 4th edn. McGraw-Hill, New York
Hanneton S, Berthoz A, Droulez J, Slotine J (1997) Does the brain use sliding variables for the control of movements? Biol Cybern 77(6):381–393
Harris C (2009) Biomimetics of human movement: functional or aesthetic? Bioinspiration Biomim 4
Hersch M, Billard A (2006) A model for imitating human reaching movements. In: Proceedings of the 1st ACM SIGCHI/SIGART conference on human-robot interaction. ACM, New York, p 342
Hill A (1910) The possible effect of the aggregation of the molecules of hæmoglobin. J Physiol 40:4–7
Howard M, Klanke S, Gienger M, Goerick C, Vijayakumar S (2009) A novel method for learning policies from constrained motion data. In: Proceedings of international conference on robotics and automation (ICRA), Kobe
Ikeuchi K (2009) Dance and robotics. In: Digital human symposium, Tokyo
Ito M (1970) Neurophysiological aspects of the cerebellar motor control system. Int J Neurol 7(2):162
Kaliki RR, Davoodi R, Loeb GE (2013) Evaluation of a noninvasive command scheme for upper-limb prostheses in a virtual reality reach and grasp task. IEEE Trans Biomed Eng 60(3):792–802
Kang T, He J, Tillery S (2005) Determining natural arm configuration along a reaching trajectory. Exp Brain Res 167(3):352–361
Kar A (2010) Skeletal tracking using microsoft kinect. Methodology 1:1–11
Kawato M (1999) Internal models for motor control and trajectory planning. Curr Opin Neurobiol 9(6):718–727
Khan S, Herrmann G, Pipe T, Melhuish C, Spiers A (2010) Safe adaptive compliance control of a humanoid robotic arm with anti-windup compensation and posture control. Int J Soc Robot 2(3):1–15
Khatib O, Sentis L, Park J, Warren J (2004) Whole body dynamic behaviour and control of human-like robots. Int J Humanoid Robot 1(1):29–43
Khatib O, Demircan E, De Sapio V, Sentis L, Besier T, Delp S (2009) Robotics-based synthesis of human motion. J Physiol-Paris 103(3–5):211–219
Kormushev P, Calinon S, Caldwell D (2010) Robot motor skill coordination with EM-based reinforcement learning. In: Proceedings of IEEE/RSJ international conference on intelligent robots and systems (IROS), Taipei, pp 3232–3237
Kuo A (1995) An optimal control model for analyzing human postural balance. IEEE Trans Biomed Eng 42(1):87–101
Lackner J, Dizio P (1998) Gravitoinertial force background level affects adaptation to Coriolis force perturbations of reaching movements. J Neurophysiol 80(2):546
Lacquaniti F, Soechting J (1982) Coordination of arm and wrist motion during a reaching task. J Neurosci 2(4):399–408
Lacquaniti F, Soechting J, Terzuolo S (1986) Path constraints on point-to-point arm movements in three-dimensional space. Neuroscience 17(2):313–324
Lallée S, Pattacini U, Lemaignan S, Lenz A, Melhuish C, Natale L, Skachek S, Hamann K, Steinwender J, Sisbot EA et al (2012) Towards a platform-independent cooperative human robot interaction system: III. An architecture for learning and executing actions and shared plans. IEEE Trans Auton Mental Dev 4(3):239–253
Lee J, Chai J, Reitsma P, Hodgins J, Pollard N (2002) Interactive control of avatars animated with human motion data. ACM Trans Graph 21(3):491–500
Lee S, Kim J, Park F, Kim M, Bobrow J (2005) Newton-type algorithms for dynamics-based robot movement optimization. IEEE Trans Robot 21(4):657–667
Liarokapis MV, Artemiadis PK, Kyriakopoulos KJ (2013) Mapping human to robot motion with functional anthropomorphism for teleoperation and telemanipulation with robot arm hand systems. In: 2013 IEEE/RSJ international conference on intelligent robots and systems (IROS), Tokyo. IEEE, Piscataway, pp 2075–2075
Luo R, Shih BH, Lin TW (2013) Real time human motion imitation of anthropomorphic dual arm robot based on cartesian impedance control. In: 2013 IEEE international symposium on robotic and sensors environments (ROSE), pp 25–30. doi:10.1109/ROSE.2013.6698413
Luo Z, Svinin M, Ohta K, Odashima T, Hosoe S (2004) On optimality of human arm movements. In: IEEE international conference on robotics and biomimetics (ROBIO 2004), Shenyang, 22–26 Aug 2004. IEEE, Piscataway, pp 256–261
Maus HM, Revzen S, Guckenheimer J, Ludwig C, Reger J, Seyfarth A (2015) Constructing predictive models of human running 12(103). doi:10.1098/rsif.2014.0899
Mell AG, Childress BL, Hughes RE (2005a) The effect of wearing a wrist splint on shoulder kinematics during object manipulation. Arch Phys Med Rehabil 86(8):1661–1664
Mell AG, Childress BL, Hughes RE (2005b) The effect of wearing a wrist splint on shoulder kinematics during object manipulation. Arch Phys Med Rehabil 86(8):1661–4. doi:10.1016/j.apmr.2005.02.008. http://www.ncbi.nlm.nih.gov/pubmed/16084823
Mellinger D, Michael N, Kumar V (2012) Trajectory generation and control for precise aggressive maneuvers with quadrotors. Int J Robot Res. doi:10.1177/0278364911434236
Meltzoff A, Moore M (1997) Explaining facial imitation: A theoretical model. Early Dev Parent 6(3–4):179–192
Menache A (2000) Understanding motion capture for computer animation and video games. Morgan Kaufmann, San Diego
Metcalf CD, Robinson R, Malpass AJ, Bogle TP, Dell T, Harris C, Demain SH et al (2013) Markerless motion capture and measurement of hand kinematics: validation and application to home-based upper limb rehabilitation. IEEE Trans Biomed Eng 60(8):2184–2192
Meyer D, Abrams R, Kornblum S, Wright C, Smith J (1988) Optimality in human motor performance: ideal control of rapid aimed movements. Psychol Rev 5:340–370
Mistry M, Mohajerian P, Schaal S (2005) Arm experiments with joint space force fields using an exoskeleton robot. In: Proceedings of the 9th international conference of rehabilitation robotics, Chicago, p 408
Mitrovic D, Klanke S, Vijayakumar S (2010) Adaptive optimal feedback control with learned internal dynamics models. In: Sigaud O, Peters J (eds) From motor learning to interaction learning in robots. Studies in Computational Intelligence. Springer, Berlin/Heidelberg, pp 65–84
Montagnani F, Controzzi M, Cipriani C (2015) Is it finger or wrist dexterity that is missing in current hand prostheses? IEEE Trans Neural Syst Rehabil Eng 23(4):600–609. doi:10.1109/TNSRE.2015.2398112
Morasso P (1981) Spatial control of arm movements. Exp Brain Res 42(2):223–227
Mussa-Ivaldi F, Patton J (2000) Robots can teach people how to move their arm. In: Proceedings of IEEE international conference on robotics & automation 2000, San Francisco, vol 1. IEEE, Piscataway, pp 300–305
Muybridge E (1881) The attitudes of animals in motion: a series of photographs illustrating the consecutive positions assumed by animals in performing various movements. CAU, San Francisco
Muybridge E (1883) The attitudes of animals in motion. J Frankl Inst 115(4):260–274
Nakanishi J, Cory R, Mistry M, Peters J, Schaal S (2008) Operational space control: a theoretical and empirical comparison. Int J Robot Res 27(6):737–757
Nakaoka S, Nakazawa A, Kanehiro F, Kaneko K, Morisawa M, Hirukawa H, Ikeuchi K (2007) Learning from observation paradigm: leg task models for enabling a biped humanoid robot to imitate human dances. Int J Robot Res 26(8):829
Nakazawa A, Nakaoka S, Ikeuchi K, Yokoi K (2002) Imitating human dance motions through motion structure analysis. In: IEEE/RSJ International Conference on Intelligent Robots and System 2002, Lausanne, vol 3
Park G, Ra S, Kim C, Song J (2008) Imitation learning of robot movement using evolutionary algorithm. In: Proceedings of the 17th IFAC work congress, Seoul, vol 17, part 1
Pastor P, Hoffmann H, Asfour T, Schaal S (2009) Learning and generalization of motor skills by learning from demonstration. In: IEEE international conference on robotics and automation 2009 (ICRA’09), Kobe. IEEE, Piscataway, pp 763–768
Patton J, Kovic M, Mussa-Ivaldi F (2006) Custom-designed haptic training for restoring reaching ability to individuals with poststroke hemiparesis. J Rehabil Res Dev 43(5):643
Peters J, Schaal S (2008) Learning to control in operational space. Int J Robot Res 27(2):197
Pollard N, Hodgins J, Riley M, Atkeson C (2002) Adapting human motion for the control of a humanoid robot. In: Proceedings of the 2002 IEEE international conference on robotics and automation, Washington, DC
Pontryagin L (1962) The mathematical theory of optimal processes. Interscience, New York
Ramos OE, Mansard N, Stasse O, Benazeth C, Hak S, Saab L (2015) Dancing humanoid robots: systematic use of OSID to compute dynamically consistent movements following a motion capture pattern. IEEE Robot Autom Mag 22(4):16–26. doi:10.1109/MRA.2015.2415048. IEEE Journals & Magazines
Rengifo C, Plestan F, Aoustin Y (2008) Optimal control of a neuromusculoskeletal model: a second order sliding mode solution. In: International workshop on variable structure systems, Antalya, pp 55–60
Roach NT, Venkadesan M, Rainbow MJ, Lieberman DE (2013) Elastic energy storage in the shoulder and the evolution of high-speed throwing in homo. Nature 498(7455):483–486
Ruchanurucks M (2015) Humanoid robot upper body motion generation using b-spline-based functions. Robotica 33(04):705–720
Ryu J, Iii WPC, Askew LJ, An Kn, Chao EYS (1991) Functional ranges of motion of the wrist joint. J Hand Surg 16:409–419
Saegusa R, Metta G, Sandini G, Sakka S (2008) Active motor babbling for sensory-motor learning. In: 2008 IEEE international conference on robotics and biomimetics (ROBIO2008), Bangkok, 14–17 Dec
Safonova A, Pollard N, Hodgins J (2003) Optimizing human motion for the control of a humanoid robot. In: Proceedings of applied mathematics and applications of mathematics, Nice, pp 155–165
Schaal S (2006) Dynamic movement primitives-a framework for motor control in humans and humanoid robotics. In: Kimura H, Tsuchiya K, Ishiguro A, Witte H (eds) Adaptive motion of animals and machines. Springer, Tokyo, pp 261–280
Schaal S, Schweighofer N (2005) Computational motor control in humans and robots. Curr Opin Neurobiol 15:675–682
Schaal S, Ijspeert A, Billard A (2003) Computational approaches to motor learning by imitation. Philos Trans R Soc of Lond B 358(1431):537–547
Sentis L, Khatib O (2005) Synthesis of whole body behaviors through hierarchical control of behavioural primitives. Int J Humanoid Robot 2(4):505–518
Sholukha V, Bonnechere B, Salvia P, Moiseev F, Rooze M, Jan SVS (2013) Model-based approach for human kinematics reconstruction from markerless and marker-based motion analysis systems. J Biomech 46(14):2363–2371
Siciliano B, Khatib O (2008) Springer handbook of robotics. Springer, Berlin
Slotine J, Li W (1991) Applied nonlinear control. Prentice Hall, Englewood Cliffs
Soechting J, Flanders M (1998) Movement planning: kinematics, dynamics, both or neither. In: Harris LR, Jenkin M (eds) Vision and action. Cambridge University, Cambridge, pp 352–371
Sundaresan A, Chellappa R (2005) Markerless motion capture using multiple cameras. In: Computer vision for interactive and intelligent environment 2005, pp 15–26. doi:10.1109/CVIIE.2005.13
Systems C (2015) Cyberglove. http://www.cyberglovesystems.com/
Takamatsu J, Ogawara K, Kimura H, Ikeuchi K (2007) Recognizing assembly tasks through human demonstration. Int J Robot Res 26(7):641–659
Teachasrisaksakul K, Zhang Z, Yang GZ, Lo B (2015) Imitation of dynamic walking with BSN for humanoid robot. IEEE J Biomed Health Inform 19(3):794–802
Tee K, Franklin D, Kawato M, Milner T, Burdet E (2010) Concurrent adaptation of force and impedance in the redundant muscle system. Biol Cybern 102(1):31–44
Todorov E (2004) Optimality principles in sensorimotor control. Nat Neurosci 7(9):907–915
Todorov E, Jordan M (2002) Optimal feedback control as a theory of motor coordination. Nat Neurosci 5(11):1226–1235
Trew M, Everett T (2001) Human movement: an introductory text. Elsevier Health Sciences, Edinburgh/New York
Ude A, Man C, Riley M, Atkeson C (2000) Automatic generation of kinematic models for the conversion of human motion capture data into humanoid robot motion. In: Proceedings of the first IEEE-RAS conference on humanoid robotics (Humanoids 2000), Massachusetts Institute of Technology, Cambridge
Uno Y, Kwato M, Suzuki R (1989) Formation and control of optimal trajectory in human multijoint arm movement. Biol Cybern 26:109–124
Vicon (2015) Vicon motion capture@ONLINE. http://www.vicon.com
Woodworth RS (1899) The accuracy of voluntary movements. Psychol Rev, Monogr 3:54–59
XSens (2015) Xsens intertial motion capture @ONLINE. https://www.xsens.com/products/mti-10-series/
Yamane K, Kuffner J, Hodgins J (2004) Synthesizing animations of human manipulation tasks. ACM Trans Graph (TOG) 23(3):532–539
Zajac F (1989) Muscle and tendon: properties, models, scaling and application to biomechanics and motor control. Crit Rev Biomed Eng 17(4):359–411
Zhou H, Hu H (2008) Human motion tracking for rehabilitationA survey. Biomed Signal Process Control 3(1):1–18. doi:10.1016/j.bspc.2007.09.001. http://linkinghub.elsevier.com/retrieve/pii/S1746809407000778
Zordan V, Van Der Horst N (2003) Mapping optical motion capture data to skeletal motion using a physical model. In: Proceedings of the 2003 ACM SIGGRAPH/Eurographics symposium on computer animation, Eurographics Association, pp 245–250
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Spiers, A., Khan, S.G., Herrmann, G. (2016). Human Motion. In: Biologically Inspired Control of Humanoid Robot Arms. Springer, Cham. https://doi.org/10.1007/978-3-319-30160-0_3
Download citation
DOI: https://doi.org/10.1007/978-3-319-30160-0_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-30158-7
Online ISBN: 978-3-319-30160-0
eBook Packages: EngineeringEngineering (R0)