Haptic Identification of Surfaces as Fields of Force

Abstract

Chib, Vikram S., James L. Patton, Kevin M. Lynch, and Ferdinando A. Mussa-Ivaldi. Haptic identification of surfaces as fields of force. J Neurophysiol 95: 1068 -1077, 2006. First published October 5, 2005 doi:10.1152/jn.00610.2005. The ability to discriminate an object's shape and mechanical properties from touch is one of the most fundamental somatosensory functions. When exploring physical properties of an object, such as stiffness and curvature, humans probe the object's surface and obtain information from the many sensory receptors in their upper limbs. This sensory information is critical for the guidance of actions. We studied how humans acquire an internal representation of the shape and mechanical properties of surfaces and how this information affects the execution of trajectories over the surface. Experiments involved subjects executing trajectories while holding a planar manipulandum that renders planar virtual objects with variable shape and mechanical properties. Subjects were instructed to make reaching movements with the hand between points on the boundary of a curved virtual disk of varying stiffness and curvature. The results suggest two classifications of adaptive responses: force perturbations and object boundaries. In the first case, a rectilinear hand movement is enforced by opposing the interaction forces. In the second case, the trajectory conforms to the object boundary so as to reduce interaction forces. While this dichotomy is evident for very rigid and very soft objects, the likelihood of an object boundary classification depended, in a smooth and monotonic way, on the average force experienced during the initial movements. Furthermore, the observed response across a variety of stiffness values lead to a constant average interaction force after adaptation. This suggests that the nervous system may select from the two responses through a mechanism that attempts to establish a constant interaction force.

Vestibular benefits to task savings in motor adaptation

“…The view that adaptation is about canceling kinematic effects of a perturbation, thus that movements return to near baseline (unperturbed) conditions (e.g., a straight line), was recently challenged by Izawa et al (2008). They suggest that motor adaptation is a process of reoptimization, possibly resulting in a different trajectory in the new environment (Chib et al 2006;Izawa et al 2008). Our results support this notion.…”

Reference Adaptation for Robots in Physical Interactions With Unknown Environments

“…With more simulation studies, it can be further shown that when there is no interaction force, the equilibrium reference trajectory and the equilibrium actual trajectory will be identical to the task trajectory. This is similar to the human experiment results observed in [13], where it shows that humans tend to make compensatory movements with small interaction forces, and seek a trade-off between tracking errors and interaction forces in force fields with moderate stiffness. Based on the above observations, the proposed method could be used for force boundary (object surface) exploration and environment identification.…”

“…In recent studies, how to obtain an impedance model and a reference trajectory that result in desired interaction performance has attracted much attention. To understand the mechanisms that humans use in physical interactions with environments, neuroscientists have investigated human motor control and adaptation using controlled force fields [11], [12], [13], [14]. It has been shown that the central nervous system (CNS) of humans has an excellent ability to repetitively adjust and tune the motion and impedance of the limb subject to changing environments and uncertain internal dynamics.…”

Use-Dependent and Error-Based Learning of Motor Behaviors

“…For example, the curvature of a movement, induced by the presence of an obstacle, influences the curvature of the next movement, even when the obstacle has been removed (Jax and Rosenbaum, 2007). Similarly, when learning to move along a curved force channel, participants exhibit force field adaptation against the channel, as well as changes in the planned curvature of the movement (Chib et al, 2006). Finally, usedependent learning can explain why the motor system arrives at seemingly nonoptimal solutions when adapting to novel dynamics in redundant tasks, as observed in experiment 3 (Scheidt et al, 2005;Diedrichsen, 2007).…”