Gaze Control-Based Navigation Architecture for Humanoid Robots in a Dynamic Environment
Due to the limited information from the environment using a local vision sensor, gaze control research is very important for humanoid robots. In addition, multiple objectives for navigation have interactive relationships among them. From this point of view, this paper proposes a gaze control-based navigation architecture using fuzzy integral and fuzzy measure for humanoid robots. Four criteria are employed along with their partial evaluation functions in order to determine the final gaze direction. By employing fuzzy integral approach for the global evaluation for candidate gaze directions, effective gaze control considering the interactive phenomena among criteria is accomplished and verified through a simulation using a developed simulator for HanSaRam-IX (HSR-IX).
Keywordsgaze control Choquet fuzzy integral preference-based selection algorithm univector field method
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- 1.Akachi, K., Kaneko, K., Kanehira, N., Ota, S., Miyamori, G., Hirata, M., Kajita, S., Kanehiro, F.: Development of humanoid robot HRP-3P. In: Proc. IEEE-RAS Int. Conf. Humanoid Robots, Tsukuba, Japan, pp. 50–55 (December 2005)Google Scholar
- 5.Andreopoulos, A., Hasler, S., Wersing, H., Janssen, H., Tsotsos, J.K., Körner, E.: Active 3D object localization using a humanoid robot. IEEE Trans. Robot. 27(1) (February 2011)Google Scholar
- 8.Lidoris, G., Kuhnlenz, K., Wollherr, D., Buss, M.: Information-based gaze direction planning algorithm for SLAM. In: 2006 6th IEEE-RAS Int. Conf. Humanoid Robots, Genova, Italy, pp. 302–307 (December 2006)Google Scholar
- 14.Bailey, T.: Mobile robot localization and mapping in extensive outdoor environments. Doct. Thesis, Univ. Sydney, Australia (2003)Google Scholar
- 15.Sugeno, M.: Theory of fuzzy integrals and its applications. Doct. Thesis, Tokyo Institute of Technology (1974)Google Scholar
- 18.Yoo, J.-K., Kim, J.-H.: Navigation framework for humanoid robots integrating gaze control and modified-univector field method to avoid dynamic obstacles. In: Proc. of IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, Taipei, Taiwan, pp. 1683–1689 (October 2010)Google Scholar