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Computación y Sistemas

Print version ISSN 1405-5546

Comp. y Sist. vol.19 n.3 México Jul./Sep. 2015

 

Artículos

 

Autonomous Motion Planning for Avatar Limbs

 

Cristian E. Boyain y Goytia Luna1, Andrés Méndez Vázquez1, Marco Antonio Ramos Corchado2

 

1 Instituto Politécnico Nacional, Centro de Investigación y Estudios Avanzados, Jalisco, México. cboyain@gdl.cinvestav.mx, amendez@gdl.cinvestav.mx

2 Universidad Autónoma del Estado de México, Toluca, Estado de México, México. marco.corchado@gmail.com

Corresponding author is Cristian E. Boyain y Goytia Luna.

 

Article received on 05/12/2014.
Accepted on 09/04/2015.

 

Abstract

In this work, a new algorithm for autonomous avatar motion is presented. The new algorithm is based in the Rapidly-exploring Random Tree (RRT) and an appropriate ontology. It uses a novel approach for calculating the motion sequence planning for the different avatar limbs: legs or arms. First, the algorithm uses the information stored in the ontology concerning the avatar structure and the Degrees Of Freedom (DOFs) to obtain the basic actions for motion planning. Second, this information is used to perform the growth process in the RRT algorithm. Then, all this information is used to produce planning. The plans are generated by a random search for possible motions that respect the structural restrictions of the avatar on kinesiology studies. To avoid a big configuration space search, exploration, exploitation, and hill climbing are used in order to obtain motion plans.

Keywords: Avatar, rapidly-exploring random tree, degree of freedom, ontology, kinesiology.

 

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Acknowledgements

This work has been funded by CONACYT scholarship 227266/212740.

 

References

1. Garro, B. A., Sossa, H., & Vázquez, R. A. (2007). Evolving ant colony system for optimizing path planning in mobile robots. IEEE Conference on Electronics, Robotics and Automotive Mechanics, pp. 444-449, doi: 10.1109/ICSPC.2007.4728416.         [ Links ]

2. Baerlocher, P. & Boulic, R. (1998). Task-priority formulations for the kinematic control of highly redundant articulated structures. IEEE International Conference on Intelligent Robots and Systems, pp. 323-329.         [ Links ]

3. Brock, O. & Khatib, O. (2000). Real-time replanning in high-dimensional configuration spaces using sets of homotopic paths. International Conference on Robotics and Automation, pp. 550-555, doi: 10.1109/ROBOT.2000.844111.         [ Links ]

4. Ma, C., Li, W., Yang, Y., & Chang, L. (1995). Robot motion planning with many degrees of freedom. IEEE International Conference on System, Man and Cybernetics, Vol. 1, pp. 892-897, doi: 10.1109/ICSMC.1995.537880.         [ Links ]

5. Choi, J. & Amir, E. (2007). Factor-guided motion planning for a robot arm. IEEE International Conference on Intelligent Robots and Systems, pp. 27-32, doi: 10.1109/IROS.2007.4399555.         [ Links ]

6. Ferguson, D., Kalra, N., & Stentz, A. (2006). Replanning with RRTs. IEEE International Conference on Robotics and Automation, pp. 1243-1248, doi: 10.1109/ROBOT.2006.1641879.         [ Links ]

7. Plaku, E., Kavraki, L.E., & Vardi, M.Y. (2010). Real-time inverse kinematics of the human arm. IEEE Transactions on Robotics, Vol. 26, No. 3, pp. 469-482.         [ Links ]

8. Ferguson, D. & Stentz, A. (2007). Anytime, dynamic planning in high-dimensional search spaces. IEEE International Conference on Robotics and Automation, pp. 1310-1315, doi: 10.1109/ROBOT.2007.363166.         [ Links ]

9. Arechavaleta, G., Esteves, C., & Laumond, J.P. (2004). Planning fine motions for a digital factotum. IEEE International Conference on Intelligent Robotics and Systems, Vol. 1, pp. 822-827.         [ Links ]

10. Gerke, M. (1999). Genetic path planning for mobile robots. American Control Conference, Vol. 4, pp. 2424-2429, doi: 10.1109/ACC.1999.786483.         [ Links ]

11. Orozco, H.R., Ramos, F., Zaragoza, J., & Thalmann, D. (2007). Avatars animation using reinforcement learning in 3d distributed dynamic virtual environments. International Conference on Logic Applied to Technology (LAPTEC), pp. 67-84 doi: 10.3233/978-1-58603-936-3-67.         [ Links ]

12. Kavraki, L.E., Svestka, P., Latombe, J.-C., & Overmars, M.H. (1996). Probabilistic roadmaps for path planning in high-dimensional configuration spaces. IEEE Transactions on Robotics and Automation, Vol. 12, No. 4, pp. 566-580, doi: 10.1109/70.508439.         [ Links ]

13. LaValle, S.M. (1998). Rapidly-exploring random trees: A new tool for path planning. Department of Computer Science, Iowa State University.         [ Links ]

14. LaValle, S.M. (2006). Planning Algorithms. Cambridge University Press.         [ Links ]

15. Luttgens, K. & Hamilton, N. (2002). Kinesiology -Scientific Basis of Human Motion. Mc Graw Hill.         [ Links ]

16. Kallmann, M., Aubel, A., Abaci, T., & Thalmann, D. (2003). Planning collision-free reaching motions for interactive object manipulation and grasping. Eurographics, Vol. 22, No. 3, pp. 313-322, doi: 10.1111/1467-8659.00678.         [ Links ]

17. Mohamad, M.M., Taylor, N.K., & Dunningan, M.W. (2006). Articulated robot motion planning using ant colony optimization. IEEE Conference on International Intelligent Systems, pp. 690-695, doi: 10.1109/IS.2006.348503.         [ Links ]

18. Uc, M., Rodríguez, A., & Ramos, F. (2007). Reinforcement learning and dynamic planning applied to virtual humans animation. 4th International Conference on Electrical and Electronics Engineering, pp. 169-172, doi: 10.1109/IS.2006.348503.         [ Links ]

19. Russell, S. & Norvig, P. (2002). Artificial Intelligence: A Modern Approach. Prentice Hall.         [ Links ]

20. Tolani, D. & Badler, N.I. (1996). Real-time inverse kinematics of the human arm. Presence, Vol. 5, No. 4, pp. 393-401.         [ Links ]

21. Koga, Y., Kondo, K., Kuffner, J., & Latmobe, J.C. (1994). Planning motion with intentions. International Conference on Computer Graphics and Interactive Techniques, doi: 10.1145/192161.192266.         [ Links ]

22. Yoshida, E. (2005). Humanoid motion planning using multi-level DOF exploitation based on randomized method. IEEE International Conference on Intelligent Robots and Systems, pp. 3378-3383, doi: 10.1109/IROS.2005.1544954.         [ Links ]

23. Arenas-Mena, J.C., Hayet, J.B., & Esteves, C. (2012). A motion capture based Planner for virtual characters navigating in 3D environments. Computación y Sistemas, Vol. 16, No. 4.         [ Links ]

24. Choi, J. & Amir, E. (2009). Combining Planning and Motion Planning. IEEE International Conference on Robotics and Automation, Kobe, Japan, doi: 10.1109/ROBOT.2009.5152872.         [ Links ]

25. Plaku, E. & Hager, G.D. (2010). Sampling-based Motion and Symbolic Action Planning with Geometric and Differential Constraints. IEEE International Conference on Robotics and Automation, Alaska, USA, doi: 10.1109/ROBOT.2010.5509563.         [ Links ]

26. Ding, X. & Fang, C. (2013). A Novel Method of Motion Planning for an Anthropomorphic Arm Based on Movement Primitives. IEEE/ASME Transactions on Mechatronics, Vol 18, No. 2, pp. 624-636, doi: 10.1109/TMECH.2012.2197405.         [ Links ]

27. Akgun, B. & Stilman, M. (2011). Sampling Heuristics for Optimal Motion Planning in High Dimensions. IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2640-2645, California, USA, doi: 10.1109/IROS.2011.6095077.         [ Links ]

28. Islam, F., Nasir, J., Malik, U., Ayaz, Y., & Hasan, O. (2012). RRT*-Smart: Rapid convergence implementation of RRT* towards optimal solution. IEEE International Conference on Mechatronics and Automation, Chengdu, China, doi: 10.1109/ICMA.2012.6284384.         [ Links ]

29. Xie, B., Zhao, J., & Liu, Y. (2011). Human-like Motion Planning for Robotics Arm System. International Conference on Advanced Robotics, pp. 88-93, Tallinn, Estonia, doi: 10.1109/ICAR.2011.6088543.         [ Links ]

30. Zong, D., Li, C., Xia, S., & Wang, Z. (2012). Planning interactive task for intelligent characters. Computer Animation and Virtual Worlds, Vol. 23, No. 6, pp. 547-55, doi: 10.1002/cav.1470.         [ Links ]

31. Zhang, L., Pan, J., & Manocha, D. (2009). Motion Planning of Human-like Robots using Constrained Coordination. IEEE International Conference on Humanoid Robots, pp. 188-195, Paris, France, doi: 10.1109/ICHR.2009.5379545.         [ Links ]

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