Predictability and Robustness in the Manipulation of Dynamically Complex Objects

Abstract

Manipulation of complex objects and tools is a hallmark of many activities of daily living, but how the human neuromotor control system interacts with such objects is not well understood. Even the seemingly simple task of transporting a cup of coffee without spilling creates complex interaction forces that humans need to compensate for. Predicting the behavior of an underactuated object with nonlinear fluid dynamics based on an internal model appears daunting. Hence, this research tests the hypothesis that humans learn strategies that make interactions predictable and robust to inaccuracies in neural representations of object dynamics. The task of moving a cup of coffee is modeled with a cart-and-pendulum system that is rendered in a virtual environment, where subjects interact with a virtual cup with a rolling ball inside using a robotic manipulandum. To gain insight into human control strategies, we operationalize predictability and robustness to permit quantitative theory-based assessment. Predictability is quantified by the mutual information between the applied force and the object dynamics; robustness is quantified by the energy margin away from failure. Three studies are reviewed that show how with practice subjects develop movement strategies that are predictable and robust. Alternative criteria, common for free movement, such as maximization of smoothness and minimization of force, do not account for the observed data. As manual dexterity is compromised in many individuals with neurological disorders, the experimental paradigm and its analyses are a promising platform to gain insights into neurological diseases, such as dystonia and multiple sclerosis, as well as healthy aging.

Predictability, force, and (anti)resonance in complex object control

“…Extending previous work by Sternad and colleagues (Bazzi et al 2018;Hasson et al 2012a;Nasseroleslami et al 2014;Sternad and Hasson 2016), this paper investigates continuous manipulation of an underactuated object with nonlinear internal dynamics. The task of moving a bowl-shaped cup with a ball inside was implemented in a virtual environment, using a cart-and-pendulum model to mimic the ball rolling in the moving cup.…”

“…Similar to Hasson et al (2012aHasson et al ( , 2012b, Nasseroleslami et al (2014), and Sternad and Hasson (2016), the cup-and-ball system was modeled as a ball sliding in a semicircular cup (Fig. 1A).…”

Separating neural influences from peripheral mechanics: the speed-curvature relation in mechanically constrained actions

“…Long communication delays are a core challenge of human motor control. Coping with these delays requires a controller that favors predictability, even over energetic cost in some cases (Bazzi et al 2018;Koeppen et al 2017;Maurice et al 2018a;Nasseroleslami et al 2014;Sternad and Hasson 2016). Smoothness quantified by minimizing mean-squared jerk provides a measure of predictability, and maximizing smoothness has been shown to account for the coordination of simple reaching movements, including an account for the two-thirds power law (Flash and Hogan 1985;Richardson and Flash 2002;Schaal and Sternad 2001;Sternad and Schaal 1999;Viviani and Flash 1995).…”

“…Slow neural transmission and muscle response implies that humans have to rely heavily on feed-forward (i.e., predictive) control, especially when physically interacting with objects and environments where bidirectional interaction forces arise. Prior work on the control of dynamically complex objects showed that humans adjust their behavior to prioritize predictability of the object dynamics (Bazzi et al 2018;Maurice et al 2018a;Nasseroleslami et al 2014;Sternad and Hasson 2016).…”

Human control of complex objects: towards more dexterous robots

“…To turn this task into an experimental paradigm that can provide insights into control, the complexity of the object was significantly reduced, yet the essential elements of this dynamical system were retained: underactuation and nonlinearity, where the latter could induce chaotic behavior. The cup was simplified to a 2-dimensional semicircular arc with a ball rolling inside [28,29], representing the sloshing coffee (Fig. 1A).…”