Passive Motion Paradigm: An Alternative to Optimal Control

Abstract

In the last years, optimal control theory (OCT) has emerged as the leading approach for investigating neural control of movement and motor cognition for two complementary research lines: behavioral neuroscience and humanoid robotics. In both cases, there are general problems that need to be addressed, such as the “degrees of freedom (DoFs) problem,” the common core of production, observation, reasoning, and learning of “actions.” OCT, directly derived from engineering design techniques of control systems quantifies task goals as “cost functions” and uses the sophisticated formal tools of optimal control to obtain desired behavior (and predictions). We propose an alternative “softer” approach passive motion paradigm (PMP) that we believe is closer to the biomechanics and cybernetics of action. The basic idea is that actions (overt as well as covert) are the consequences of an internal simulation process that “animates” the body schema with the attractor dynamics of force fields induced by the goal and task-specific constraints. This internal simulation offers the brain a way to dynamically link motor redundancy with task-oriented constraints “at runtime,” hence solving the “DoFs problem” without explicit kinematic inversion and cost function computation. We argue that the function of such computational machinery is not only restricted to shaping motor output during action execution but also to provide the self with information on the feasibility, consequence, understanding and meaning of “potential actions.” In this sense, taking into account recent developments in neuroscience (motor imagery, simulation theory of covert actions, mirror neuron system) and in embodied robotics, PMP offers a novel framework for understanding motor cognition that goes beyond the engineering control paradigm provided by OCT. Therefore, the paper is at the same time a review of the PMP rationale, as a computational theory, and a perspective presentation of how to develop it for designing better cognitive architectures.

DForC: A real-time method for reaching, tracking and obstacle avoidance in humanoid robots

“…Similar properties are also shown by a more generic framework, known in literature with the name of Passive Motion Paradigm (PMP) [13] [14] [15], which has a relevant neurobiological background that builds on the Equilibrium Point Hypothesis developed in the 60's by Bizzi [16]. For the purpose of this paper, PMP can be thought of as one particular variant of the transpose Jacobian method to 2012 12th IEEE-RAS International Conference on Humanoid Robots Nov.29-Dec.1, 2012. Business Innovation Center Osaka, Japan Fig.…”

A predictive processing theory of motivation

“…In particular, the claim that motivational mental states' guidance role is achieved by enabling the efficient computation of cost functions should be treated with suspicion. Many working roboticists (Feldman 2009 andMohan andMorasso 2011), as well as neuroscientists and philosophers (Friston 2011;Clark 2016: p. 132) have branded explicit cost-function-based solutions to the problem of efficient motor selection inflexible and biologically unrealistic. As Mohan and Marasso put the issue, …such engineering paradigms were designed for high bandwidth, inflexible, consistent systems with precision sensors.…”

Control of redundant pointing movements involving the wrist and forearm

“…The passive motion paradigm (PMP) has been proposed as an alternative to optimal control (Mohan and Morasso 2011) and was recently applied to the problem of pointing with the wrist and forearm (Tommasino and Campolo 2017). This strategy "offers the brain a way to dynamically link motor redundancy with task-oriented constraints 'at runtime,' hence solving the 'DoFs problem' without explicit kinematic inversion and cost function computation" (Mohan and Morasso 2011). The basic idea is that task goals are reformulated as attractor fields that pull the end-effector toward the goal, naturally resulting in joint displacements that satisfy the dynamic constraints imposed by joint impedance, including interaction torques.…”