Motor planning explains human behaviour in tasks with multiple solutions
How does the human central nervous system generate appropriate movements to accomplish complex motor tasks, while adapting to the changing environmental conditions? The traditional motor control research has focused on simplified tasks in which healthy human subjects were found to utilise a single solution. In this chapter we present recent works that have examined motor control and learning in richer and more natural environments. Unlike the simplified tasks, humans use multiple solutions to solve these tasks, often switching between these solutions within trials. We exhibit the requirement of an explicit planning stage in sensorimotor control models to explain these behaviours. Behavioural experiments investigating motor planning in humans are necessary to understand all the aspects of the non-conventional control and optimisation used by humans, which will also help robots to work in complex environments such as those humans live in.
planning multiple solutions human motor control computational modelling motor memory