Body Mechanics, Optimality, and Sensory Feedback in the Human Control of Complex Objects

Author:

Razavian Reza Sharif1,Sadeghi Mohsen2,Bazzi Salah3,Nayeem Rashida4,Sternad Dagmar5

Affiliation:

1. Department of Mechanical Engineering, Northern Arizona University, Flagstaff, AZ 86011, U.S.A. razavian.reza@nau.edu

2. Department of Biology and Department of Electrical and Computer Engineering, Northeastern University, Boston, MA 02115, U.S.A. m.sadeghi@northeastern.edu

3. Department of Electrical and Computer Engineering and Institute for Experiential Robotics, Northeastern University, Boston, MA 02115, U.S.A. s.bazzi@northeastern.edu

4. Department of Electrical and Computer Engineering, Northeastern University, Boston, MA 02115, U.S.A. nayeem.r@northeastern.edu

5. Departments of Biology, Electrical and Computer Engineering, and Physics, Institute for Experiential Robotics, Northeastern University, Boston, MA 02115, U.S.A. d.sternad@northeastern.edu

Abstract

AbstractHumans are adept at a wide variety of motor skills, including the handling of complex objects and using tools. Advances to understand the control of voluntary goal-directed movements have focused on simple behaviors such as reaching, uncoupled to any additional object dynamics. Under these simplified conditions, basic elements of motor control, such as the roles of body mechanics, objective functions, and sensory feedback, have been characterized. However, these elements have mostly been examined in isolation, and the interactions between these elements have received less attention. This study examined a task with internal dynamics, inspired by the daily skill of transporting a cup of coffee, with additional expected or unexpected perturbations to probe the structure of the controller. Using optimal feedback control (OFC) as the basis, it proved necessary to endow the model of the body with mechanical impedance to generate the kinematic features observed in the human experimental data. The addition of mechanical impedance revealed that simulated movements were no longer sensitively dependent on the objective function, a highly debated cornerstone of optimal control. Further, feedforward replay of the control inputs was similarly successful in coping with perturbations as when feedback, or sensory information, was included. These findings suggest that when the control model incorporates a representation of the mechanical properties of the limb, that is, embodies its dynamics, the specific objective function and sensory feedback become less critical, and complex interactions with dynamic objects can be successfully managed.

Publisher

MIT Press

Subject

Cognitive Neuroscience,Arts and Humanities (miscellaneous)

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