Abstract
In order to increase the robustness of space robot teleoperation system and good operational performance, the article design a set of haptic feedback system based on hand controller data glove and active vision system, which depend on the Pan-Tilt-Zoom (PTZ) camera and Kinect camera. It makes operators have the feeling of immersive. This system requires two operator cooperation, one processing Active Vision tracking and image processing, one controlling the movement of robot under the good perception environment. At the same time, Good interpersonal interface design to alleviate the pressure of the operator, in order to study the real space teleoperation scene, we use the software to set the delay system to make the operator to verify the performance of the system in the case of delay. The experiments show that no matter in the presence or absence of delay, the system completes the tasks at a high success rate.
This work is jointly supported by the National Natural Science Foundation of China (Grants No: 61075027, 91120011, 61210013), Tsinghua Self-innovation Project (Grant No: 20111081111) and Graduate student innovation fund project in Shanghai. Project approval no: JWCXSL1202.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Sheridan TB (1993) Space teleoperation through time delay: review and prognosis. In: IEEE Trans Robot Autom 9(5):592–606
Lee S (1993) Modeling, design, and evaluation of advanced teleoperator control systems with short time delay. IEEE Trans Robot Autom 9(5):607–623
Azorin JM, Reinoso O et al (2004) Generalized control method by state convergence for teleoperation systems with time delay. Automatica 40:1575–1582 (Elsevier)
Yoon WK, Goshozono T et al (2004) Model-based space robot teleoperation of ETS-VII manipulator. IEEE Trans Robot Autom 20(3):602–612
Liu YY, Liu HP et al (2011) GPU accelerate the online k-means clustering particle filter tracking algorithm. J Cent S Univ (JCR Sci Ed) 42 supplement 9:1–7
Jun M, Tsuyoshi K (2000) An active vision system for real time traffic sign recognition In: IEEE intelligent transportation systems conference proceedings Dearborn (MI), pp 52–57. Oct 1–3
Ma S (1996) A self-calibration technique for active vision systems. IEEE Trans Robot Autom 12(1):114–120
Pérez P, Hue C, Vermaak J et al (2002) Color based probabilistic tracking. In Proceedings of the 7th European conference on computer vision, vol 2002, no (1), Copenhagen. pp 661–675
Kim Z (2008) Real time object tracking based on dynamic feature grouping with background subtraction. In: IEEE conference on computer vision and pattern recognition, Anchorage. pp 1–8. http://www.openni.org
Blake A, Isard M et al (1994) Learning to track curves in motion. In: Proceedings of the IEEE conference on decision theory and control. pp 3788–3793
Black MJ, Jepson AD (1995) Eigen tracking: robust matching and tracking of articulated objects using a view-based representation. Technical report T95-00515, Xerox PARC
Doucet A, Godsill S et al (2000) On sequential Monte Carlo sampling method for Bayesian filtering. Stat Comput 10(3):197–208
Bradski GR (1998) Computer vision face tracking as a component of a perceptual user interface. In: Workshop on applications of computer vision. Princeton. pp 214–219
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Huang, C., Liu, H., Sun, F., Sheng, Y. (2014). Space Robot Teleoperation Based on Active Vision. In: Wen, Z., Li, T. (eds) Practical Applications of Intelligent Systems. Advances in Intelligent Systems and Computing, vol 279. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54927-4_22
Download citation
DOI: https://doi.org/10.1007/978-3-642-54927-4_22
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-54926-7
Online ISBN: 978-3-642-54927-4
eBook Packages: EngineeringEngineering (R0)