Home > Multivehicle Systems > 1st IFAC Workshop on Multivehicle Systems, 2006 > Team formation based on nonlinear control techniques and omnidirectional vision
Team formation based on nonlinear control techniques and omnidirectional vision
Multivehicle Systems, Volume # 1 | Part# 1
Location: Centro de Convenções da Bahia, Brazil
National Organizing Committee Chair: Anna Helena Reali Costa
International Program Committee Chair: Pedro Lima
Conference Editor: Carlos H. C. Ribeiro
Authors
Christiano Couto Gava; Raquel Frizera Vassallo; Ricardo Carelli; Teodiano Freire Bastos Filho
Identifier
10.3182/20061002-2-BR-4906.00004
Index Terms
robot cooperation,nonlinear control,omnidirectional vision
Abstract
In this work a mobile robot cooperation strategy based on computational vision is presented. Such strategy is applied to a mobile robot team formed by simple and cheap robots and a leader robot with more computational power. The leader has an omnidirectional visual system and uses color segmentation to obtain the pose of the followers. This visual information is used by a nonlinear stable controller that manages team formation. Simulations and tests were run and current results are encouraging.
References
[1] Adams, Jon (2003). Meet the zigbee standard.
Sensors Magazine.
[2] Baker, S. and S. K. Nayar (1999). A theory
of single-viewpoint catadioptric image formation.
International Journal of Computer Vision
35(2), 1-22.
[3] Das, A. K., R. Fierro, V. Kumar, J. P. Ostrowski,
J. Spletzer and C. J. Taylor (2002). A vision-based
formation control framework. In: IEEE
Transactions on Robotics and Automation.
Vol. 18. pp. 813-825.
[4] Gonzalez, R. C. and R. E. Woods (2002). Digital
Image Processing. Prentice Hall.
[5] Kelly, R., R. Carelli, J. M. I. Zannatha and
C. Monroy (2004). Control de una pandilla
de robots móviles para el seguimiento de
una constelación de puntos objetivo. In: VI
Congreso Mexicano de Robótica.
[6] Matáric, M. J., M. Nilsson and K. T. Simsarin
(1995). Cooperative multi-robot box-pushing.
In: IROS 95. Vol. 3. pp. 556-561.
[7] Nayar, S. K. (1997). Omnidirectional vision. In:
8th International Symposium on Robotics Research
.
[8] Open Source Computer Vision Library (n.d.).
at http://www.intel.com/technology/ computing/opencv/index.htm.
[9] Pereira, F. G., C. C. Gava, R. F. Vassallo and
M. Sarcinelli-Filho (2005). Calibração de sistemas
catadióptricos e detecção da pose de
robôs móveis por segmentação de imagens
omnidirecionais. In: VII SBAI.
[10] Santos-Victor, J. A., R. Carelli and S. Van Zwaan
(2002). Nonlinear visual control of remote cellular
robots. In: 10th Mediterranean Conference
on Control and Automation.
[11] Soria, C. M., R. Carelli, T. F. Bastos-Filho and
M. Sarcinelli-Filho (2003). Control de robots
celulares en base a visión artificial. In: VI
SBAI.
[12] Vassallo, R. F., L. F. Encarnação, J. A. Santos-Victor
and H. J. A. Schneebeli (2004). Bird's
eye view remapping and path following based
on omnidirectional vision. In: XV CBA.
[13] Vidal, R., O. Shakernia and S. Sastry (2004).
Following the flock. In: IEEE Robotics &
Automation Magazine. pp. 14-20.
