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Related Experiment Videos

Quantitative examinations for multi joint arm trajectory planning--using a robust calculation algorithm of the

Y Wada1, Y Kaneko, E Nakano

  • 1Nagaoka University of Technology, Niigata, Japan. ywada@nagaokaut.ac.jp

Neural Networks : the Official Journal of the International Neural Network Society
|June 20, 2001
PubMed
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This study introduces a stable numerical method for calculating optimal arm movement trajectories based on the minimum commanded torque change criterion. This new method confirms that the central nervous system likely plans movements using this criterion, improving our understanding of motor control.

Area of Science:

  • Robotics and Control Systems
  • Computational Neuroscience
  • Biomechanics

Background:

  • Previous research explored optimal theories for multi-joint arm movement trajectories, proposing criteria like minimum hand jerk and minimum angle jerk.
  • The minimum commanded torque change criterion, considering arm and muscle dynamics, is theoretically plausible but computationally challenging.
  • Existing numerical methods for this criterion often suffer from instability or unreliable optimality.

Purpose of the Study:

  • To develop a stable and accurate numerical method for calculating optimal trajectories based on the minimum commanded torque change criterion.
  • To investigate the central nervous system's (CNS) potential use of this criterion for trajectory planning.
  • To validate the proposed method by re-examining existing experimental data.

Related Experiment Videos

Main Methods:

  • A novel method using orthogonal polynomials to represent joint angle trajectories and linear iterative calculation to satisfy Euler-Poisson equations.
  • Ensuring strict adherence to boundary conditions for the calculated trajectories.
  • Numerical experiments across a wide workspace and comparison with previous computational techniques.

Main Results:

  • The proposed method stably and accurately computes optimal trajectories satisfying Euler-Poisson equations.
  • Optimal solutions were computed efficiently within a wide workspace.
  • Re-analysis of experimental data confirmed that measured arm trajectories closely match those predicted by the minimum commanded torque change criterion.

Conclusions:

  • The developed method provides a reliable way to calculate minimum commanded torque change trajectories.
  • The findings support the hypothesis that the CNS utilizes the minimum commanded torque change criterion for motor planning.
  • This research offers a significant advancement in understanding the computational principles underlying human arm movement.