Computational motor control and human factors: modeling movements in real and possible environments.

An aim of human factors research is to have models that allow for the advance design of user-friendly environments. This is still a distant dream because existing models are not yet sufficiently sophisticated. Models in the domain of motor control are a case in point, but recent developments in computational motor control suggest that the gap between the current state of modeling in this area and the desired state is shrinking. To illustrate this point, we review principles of motor control research that any model of motor control must accommodate. Then we describe a model that captures many of the capacities of actors in the everyday world, including the capacity to reach for objects in different ways depending on factors such as the ease with which different joints can rotate, the required speed of movement, and whether obstacles are present. The model relies on the ideas that goal postures are internally specified before movements are generated, that tasks are defined with flexibly ordered constraint hierarchies, and that movements can be shaped according to task demands. Actual or potential applications of this research include designing and testing possible environments where motor components play a key role.