Preparing to move: Setting initial conditions to simplify interactions with complex objects

Humans dexterously interact with a variety of objects, including those with complex internal dynamics. Even in the simple action of carrying a cup of coffee, the hand not only applies a force to the cup, but also indirectly to the liquid, which elicits complex reaction forces back on the hand. Due to underactuation and nonlinearity, the object’s dynamic response to an action sensitively depends on its initial state and can display unpredictable, even chaotic behavior. With the overarching hypothesis that subjects strive for predictable object-hand interactions, this study examined how subjects explored and prepared the dynamics of an object for subsequent execution of the target task. We specifically hypothesized that subjects find initial conditions that shorten the transients prior to reaching a stable and predictable steady state. Reaching a predictable steady state is desirable as it may reduce the need for online error corrections and facilitate feed forward control. Alternative hypotheses were that subjects seek to reduce effort, increase smoothness, and reduce risk of failure. Motivated by the task of ‘carrying a cup of coffee’, a simplified cup-and-ball model was implemented in a virtual environment. Human subjects interacted with this virtual object via a robotic manipulandum that provided force feedback. Subjects were encouraged to first explore and prepare the cup-and-ball before initiating a rhythmic movement at a specified frequency between two targets without losing the ball. Consistent with the hypotheses, subjects increased the predictability of interaction forces between hand and object and converged to a set of initial conditions followed by significantly decreased transients. The three alternative hypotheses were not supported. Surprisingly, the subjects’ strategy was more effortful and less smooth, unlike the observed behavior in simple reaching movements. Inverse dynamics of the cup-and-ball system and forward simulations with an impedance controller successfully described subjects’ behavior. The initial conditions chosen by the subjects in the experiment matched those that produced the most predictable interactions in simulation. These results present first support for the hypothesis that humans prepare the object to minimize transients and increase stability and, overall, the predictability of hand-object interactions.Author summary: Humans interact with objects that have complex dynamics every day. One example is picking up a cup filled with coffee to drink: the hand applies a force not only to the cup, but also indirectly to the liquid, which in turn acts back on the hand. These interactions can quickly become unpredictable, i.e., making it difficult for a person to control the potentially chaotic interactions in real-time. When starting such an action from rest, the object experiences start-up dynamics, or transients, that partly depend upon the initial conditions. We examined how subjects learn to identify initial conditions to shorten transients and make the ensuing interaction dynamics stable and predictable. Using a simplified model of the cup of coffee, a 2D cup with a rolling ball inside and moving on a horizontal line, subjects were encouraged to prepare the object dynamics to find the best initial conditions prior to starting a continuous transport task. Experimental and modeling results showed that with practice subjects converged to a small set of initial conditions, which decreased their transient durations, and achieved increasingly predictable interactions. The typical objectives in unconstrained tasks—to decrease effort and increase smoothness—could not be supported.