Vision-Based Online Trajectory Generation and Its Application to Catching

نویسندگان

  • Akio Namiki
  • Masatoshi Ishikawa
چکیده

In this paper a method for sensor-based online trajectory generation is proposed. This method is based on a nonlinear mapping from sensor information to a desired trajectory, and a nonlinear mapping is decided by online learning based on constraints of dynamics and kinematics. This method is applied to a catching task, and responsive and flexible motion is realized based on realtime high-speed sensory information. Experimental results about catching of a moving object is shown.

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تاریخ انتشار 2002