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Title: Body Mechanics, Optimality, and Sensory Feedback in the Human Control of Complex Objects
Abstract Humans 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.  more » « less
Award ID(s):
1825942
NSF-PAR ID:
10465767
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
Neural Computation
Volume:
35
Issue:
5
ISSN:
0899-7667
Page Range / eLocation ID:
853 to 895
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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