motrobusthet

Motrobusthet is a proposed quantitative property used to describe the resilience of motor systems—biological, robotic, or hybrid—in the face of disturbances and model uncertainty. Informally, it gauges how well a system preserves its intended motor goals, such as accuracy of a reaching movement or stability of a walking pattern, when subjected to perturbations such as unexpected forces, sensor noise, or delays in actuation.

Coined from the root "motor" and the suffix "-robusthet" akin to robustness, motrobusthet is intended as a generalizable measure across domains of motor control. It applies to systems that integrate perception, decision, and action loops, including prosthetic devices and autonomous robots.

Formal definitions vary. In many proposals, motrobusthet is computed by testing a set of perturbations and recording a performance function under nominal conditions. A common form is M = 1 - E[Δf / f0], or M = min over perturbations of f(p)/f0, depending on whether one emphasizes average or worst-case performance. Alternative formulations incorporate energy efficiency and safety margins. In practice, motrobusthet is estimated via simulation, hardware experiments, or standardized benchmarks.

It informs design and control choices, enabling comparisons between controllers, mapping of robustness across tasks, and guiding trade-offs between precision, speed, and energy use. It is used in robot manipulation, legged locomotion, exoskeletons, and rehabilitation devices, as well as studies of human motor control.

Because there is no universal definition or benchmarking suite, motrobusthet remains an emergent concept. Its utility depends on clearly specified task definitions, perturbation models, and objective functions. Ongoing work seeks to establish conventions, benchmarks, and cross-domain standards.