Shared control is an increasingly popular approach to facilitate control and communication between humans and intelligent machines. However, there is little consensus in guidelines for design and evaluation of shared control, or even in a definition of what constitutes shared control. This lack of consensus complicates cross fertilization of shared control research between different application domains. This paper provides a definition for shared control in context with previous definitions, and a set of general axioms for design and evaluation of shared control solutions. The utility of the definition and axioms are demonstrated by applying them to four application domains: automotive, robot-assisted surgery, brain-machine interfaces, and learning. Literature is discussed for each of these four domains in light of the proposed definition and axioms. Finally, to facilitate design choices for other applications, we propose a hierarchical framework for shared control that links the shared control literature with traded control, cooperative control, and other human-automation interaction methods. Future work should reveal the generalizability and utility of the proposed shared control framework in designing useful, safe, and comfortable interaction between humans and intelligent machines.

Gibo TL, Criscimagna-Hemminger SE, Okamura AM, Bastian AJ. Cerebellar motor learning: are environment dynamics more important than error size?

Gamma-aminobutyric acid (GABA) is an important retinal neurotransmitter. We studied the expression of GABA, glutamate decarboxylase 65 (GAD65) and GAD67 by immunocytochemistry and Western blot, in the retinas of control and dark-reared C57BL/6J black mice. This study asked three questions. First, is visual input necessary for the normal expression of GABA, GAD65 and GAD67? Second, can the retina recover from the effects of dark-rearing if returned to a normal light-dark cycle? Third, does BDNF prevent the influence of dark-rearing on the expression of GABA and GAD? At postnatal day 10 (P10), before eye opening, GABA immunoreactivity was present in the ganglion cell layer (GCL), in the innermost rows of the inner nuclear layer (INL) and throughout the inner plexiform layer (IPL) of control and dark-reared retinas. In P30 control retinas, GABA immunoreactivity showed similar patterns to those at P10. However, in P30 dark-reared retinas, the density of GABA-immunoreactive cells was lower in both the INL and GCL than in control retinas. In addition, visual deprivation retarded GABA immunoreactivity in the IPL. Western blot analysis showed corresponding differences in the levels of GAD65 but not of GAD67 expression between control and dark-rearing conditions. In our study, dark-rearing effects were reversed when the mice were put in normal cyclic light-dark conditions for 2 weeks. Moreover, dark-reared retinas treated with BDNF showed normal expression of both GABA and GAD65. Our data indicate that normal expression of GABA and GAD65 is dependent on visual input. Furthermore, the data suggest that BDNF controls this dependence.

When grasping and manipulating objects, people are able to efficiently modulate their grip force according to the experienced load force. Effective grip force control involves providing enough grip force to prevent the object from slipping, while avoiding excessive force to avoid damage and fatigue. During indirect object manipulation via teleoperation systems or in virtual environments, users often receive limited somatosensory feedback about objects with which they interact. This study examines the effects of force feedback, accuracy demands, and training on grip force control during object interaction in a virtual environment. The task required subjects to grasp and move a virtual object while tracking a target. When force feedback was not provided, subjects failed to couple grip and load force, a capability fundamental to direct object interaction. Subjects also exerted larger grip force without force feedback and when accuracy demands of the tracking task were high. In addition, the presence or absence of force feedback during training affected subsequent performance, even when the feedback condition was switched. Subjects' grip force control remained reminiscent of their employed grip during the initial training. These results motivate the use of force feedback during telemanipulation and highlight the effect of force feedback during training.