Abstract
In this paper, a method for vision-based online trajectory generation is proposed. The proposed method is based on a nonlinear mapping of visual information to the desired trajectory, and this nonlinear mapping is defined by learning based on constraints of dynamics and kinematics. This method is applied to a catching task, and a reactive and flexible motion is obtained owing to real-time high-speed visual information. Experimental results on catching a moving object using a high-speed vision chip system are presented.
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Namiki, A., Ishikawa, M. (2003). Vision-Based Online Trajectory Generation and Its Application to Catching. In: Bicchi, A., Prattichizzo, D., Christensen, H.I. (eds) Control Problems in Robotics. Springer Tracts in Advanced Robotics, vol 4. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36224-X_16
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DOI: https://doi.org/10.1007/3-540-36224-X_16
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