Summary
Dependable robots and teleoperation, taken in its broadest sense, require natural and friendly human-robot interaction systems. The work presented consists of a methodology for human-robot interaction based on the perception of human intention from vision and force. The vision system interprets human gestures from the integration of a stereovision and a carving system, from which it extracts a model of the human body when a person approaches the robot. The interaction can be performed by contact as well, from the perception of the forces applied to the robot either through a force sensor on the wrist or a sensing skin. The perception of human intention makes possible an intuitive interaction to modify on line the robot trajectory when required.
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References
T. Fong, I. Nourbakhsh, and K. Dautenhahn. A survey of socially interactive robots. Robotics and Autonomous Systems, 42:143–166, 2003.
A. Billard and M. Mataric. Learning human arm movements bi imitation: evaluation of a biologically inspired connectionist architecture. Robotics and Autonomous Systems, 37:1–16, 2001.
M. Frigola, J. Poyatos, A. Casals, and J. Amat. Improving robot programming flexibility through physical human-robot interaction. In IROS Workshop on Robot Programming by Demonstration, Las Vegas, USA, 2003.
J. Amat, A. Casals, and M. Frigola. Human Body Acquisition and Modeling for Persons-Humanoid Robots Cooperation. In The Third IARP Workshop on Humanoid and Human Friendly Robotics, pages 76–78, 2002.
J. Hwang, R. Arkin, and D. Kwon. Mobile robots at your fingertip: Bezier curve on-line trajectory generation for supervisory control. In IROS Workshop on robot programming by demonstration, Las Vegas, USA, 2003.
W. Son, K. Kim, B. Jang, and B. Choi. Interactive dynamic simulation schemes for articulated bodies through haptic interface. ETRI Journal, 25:25–33, 2003.
O. Khatib, et al. Human-centered robotics and interactive haptic simulation. The International Journal of Robotics Research, 2004.
T. Molet, R. Boulic, and D. Thalmann. A real-time anatomical converter for human motion capture. In Proc. 7th Eurographics Workshop on Animation and Simulation Springer Verlag, Wien, 1996.
A. Franois and G. Medioni. Adaptive colour background modelling for real-time segmentation of video streams. Technical Report, University of South California.
O. Javed, K. Shafique, and M. Shah. A hierarchical approah to robust background subtraction using color and gradient information. In Workshop on Motion and Video Computing, IEEE, pages 22–27, 2002.
T. Horprasert, D. Harwood, and L. Davis. A statistical approach for real-time robust background subtraction and shadow detection. In IEEE ICCV Frame-rate Workshop, 1999.
P. Salembier and F. Marqus. Region-based representations of image and video: Segmentation tools for multimedia services. IEEE Transactions on circuits and Systems for video technology, 9:1147–1167, 1999.
S. Cheng and M. Trivedi. Human posture estimation using voxel data for “’smart”’ airbag systems: Issues and Framework. In Intelligent Vehicles Symposium, pages 84–99, 2004.
K. Cheung, T. Kanade, and J. Bouguet. A real time system for robust 3D voxel reconstruction of human motions. In Computer Vision and Pattern Recognition Conference, 2:714–720, 2000.
J. Buades and F. Perales. Voxel matching reconstruction in real image sequences of human avatars. In 1st Ibero-American Symposium in Computer Graphics Guimaraes, Portugal, 2002.
R. Szeliski. Real-time octree generation from rotation objects. Technical Report, Cambridge Research Laboratory. 1990.
I. Mikic, M. Trivedi, E. Hunter, and P. Cosman. Articulated body posture estimation from multi-camera voxel data. Computer Vision and Pattern Recognition, 2001.
F. Caillette and T. Howard. Real-time markerless human body tracking with multiview 3D voxel reconstruction. In British Machine Vision Conference, 2:597–606, 2004.
F. Caillette and T. Howard. Real-time markerless human body tracking using colored voxels and 3D blobs. In ACM International Symposium on Mixed and Augmented Reality, pages 266–267, 2004.
I. Mikic, M. Trivedi, E. Hunter, and P. Cosman. Human body model acquisition and tracking using voxel data. International Journal of Computer Vision, 53(3):199–223, 2003.
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Frigola, M., Rodriguez, A., Amat, J., Casals, A. (2007). Computer Vision Body Modeling for Gesture Based Teleoperation. In: Ferre, M., Buss, M., Aracil, R., Melchiorri, C., Balaguer, C. (eds) Advances in Telerobotics. Springer Tracts in Advanced Robotics, vol 31. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71364-7_9
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DOI: https://doi.org/10.1007/978-3-540-71364-7_9
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