human motion simulation

Human Motion Simulation Using

Back Propagation as

Inverse Kinematics Solver

Goals 1. To make a 3D representation of a

human body. 2. To implement an inverse

kinematics solver for motion simulation.

Human Motion Simulation Using Back Propagation as Inverse Kinematics Solver


Modeling the Human Motions being simulated Inverse Kinematics Back Propagation


Human Model : The Making

The human body The skeleton The human motion

Human Model : The Skeletal System


Bones Joints Joint as Vertex Bone as Link (x1,y1,z1)

(x2,y2,z2)


Human Model : DH Convention

Given these parameters d – link offset a – link lengthα – link twist (rotation on x-axis)θ – link angle (rotation on z-axis)

Describes the position and orientation of a link with respect to a frame of reference

Models the human motion

Human Model : Forward Kinematics


Inverse Kinematics


- compute the angles of the joints to reach a desired location.

Example of Inverse Kinematics

Back Propagation Is a artificial neural network that has 3 layers,

the input layer, hidden layer and output layer.


Illustration of a back propagation neural network

Back Propagation Configuration

Number of input neurons – 24 Number of hidden layers – 2 Number of hidden neurons of each layer – 54 Number of output neurons – 54 Initial learning rate – 0.1 Final learning rate – 0.001 Initial momentum – 0.95 Final momentum – 0.2


Back Propagation as Inverse Kinematics Solver

Four back propagations were used.1. Left leg 2. Right Leg3. Left arm 4. Right arm

Each were trained using randomly generated end effector’s positions and joint angles.


Output Tolerance

82.24 84.3 81.4 81.5

16.24 15.7 18.6 18.5

0

10

20

30

40

50

60

70

80

90

Kinematics Chain

Per

cen

tag

e

Passed

Failed

Result


Left Leg Right Leg Left Arm Right Arm

Significance


•Can be used in different fields like computer animation and robotics.

•Our human model can be used as substitutes for the real humanoid robot participants into virtual environments.

Significance (Cont.)

Our human model can be used on experimenting right configurations of a human robot before building an actual robot.

Another neural network can be used as inverse kinematics solver to make a comparative study.


References

[1] Robotics Appin Knowledge Solutions; Infinity Science Press LLC Hingham, Massachusetts New Delhi; p. 14

[2] The World Book Encyclopedia, 1995 [3] The World Book Encyclopedia, 1998 [4] Scientists try to make robots more human http//www.

usatoday.com/tech/news/robotics/2006-11-22

References [5] Interactive Simulation of Stylized Human Locomotion [6] Real time Virtual Humans http://www.cis.upenn.edu/~badler/bcs/Paper.htm [7] Jack, The Making of a Virtual Human Being http://www.dp.upenn.edu/street/032097/: [8] Robot a Programmer’s Bonanza; John Blankenship and Samuel

Mishal; McGraw-Hill Companies; 2008; pp.3-6 [9] Simulation of Human Body Kinematics http:// www.cescg.org/CESCG-2000/RFilkorn/ [10] Realistic Human Simulation From Simulating real-world objects, to

creating comprehensive simulations of reality

http://www.engineer.ucla.edu/newsroom/featurednews/archive/2009/realistic-human-simulation/

[11] Human Motion Modelling and Simulation http://academic.research.microsoft.com/Paper/6012143.aspx [12] Humanoid Robots http://www.robotmatrix.org/humanoidrobot.htm

References [13]Ontology forVirtual Humans http://vrlab.cpfl.ch/~alcgarcia/VHOntology/long.html [14]CS 490 Human Motion Simulation, Philip Yen, Spring 1998

http://www.nbb.cornell.edu/neurobio/land/OldStudentProjects/cs490-97to98/yen/ [15] SOK, K. W., KIM, M., AND LEE, J. 2007. Simulating biped behaviors from human motion data. ACM Transactions on Graphics 26, 3 (July), 107:1–107:9. [16] ABDALLAH, M.; GOSWAMI, A. 2005. A biomechanically motivated two-phase

strategy for biped upright balance control. In International Conference on Robotics and Automation (ICRA), 1996–2001.

[17] History of Robots http://pages.cpsc.ucalgary.ca/~jaeger/visualMedia/robotHistory.html http://www.space.gc.ca/pdf/educator-story_robot.pdf [18] http://www.intelligent-systems.com.ar/intsyst/artis.htm [19] Humanoid robots: A New Kind of Tool http://people.csail.mit.edu/brooks/papers/IEEE-cog.pdf [20] Digital Representations of Human Movement http://design.osu.edu/carlson/history/PDFs/badler-smoliar.pdf [21] Keyframe Animation http://www.cadtutor.net/dd/bryce/anim/anim.html

References [22] Humanoid Animation http://www.ia.hiof.no/vv/pages/moduler/animation/

humanoid_a.html [23 ] Specification for a Standard VRML Humanoid http://h-anim.org/Specifications/H-Anim1.0/ [24] Motion Capture http://www.ia.hiof.no/vv/pages/moduler/animation/

motion_capture.html [25] Surface Reconstruction from Point Cloud of Human

Body by Clustering; Systems and Computers in Japan, Vol. 37, No. 11, 2006 http://www.mm.media.kyoto-u.ac.jp/research/doc/727/

Publication.pdf

References [26]Kallmann, M. (2008), Analytical inverse kinematics with

body posture control. Computer Animation and Virtual Worlds, 19: 79–91. doi: 10.1002/cav.176

[27] Modelling Inverse Kinematics in a robotic armhttp://www.mathworks.com/products/fuzzylogic/demos.html?file=/products/demos/shipping/fuzzy/invkine_codepad.html

[28] Inverse Kinematics Solution of 3DOF Planar Robot using ANFIS; Srinivasan Alavandar, M.J. Nigam; Int. J. of Computers, Communications & Control, ISSN 1841-9836, E-ISSN 1841-9844 ;Vol. III (2008), Suppl. issue: Proceedings of ICCCC 2008, pp. 150-155

[29] Forward Kinematics for Virtual Agents; Antonio Benitez R., Guillermo de los Santos T. and Daniel Vallejo R.

[30] Simulation of Betty: A Humanoid Robot with OpenGL; Meng Cheng, Lau.

[31] Robot Modeling and Kinematics. Manseur, Rachid

human motion simulation

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