Perception as a Dynamical Sensori-Motor Attraction Basin

Proceedings of the 12th International Conference on Agents and Artificial Intelligence, 2020

The modelling of cognition is playing a major role in robotics. Indeed, robots need to learn, adapt and plan their actions in order to interact with their environment. To do so, approaches like embodiment and enactivism propose to ground sensorimotor experience in the robot's body to shape the development of cognition. In this work, we focus on the role of memory during learning in a closed loop. As sensorimotor contingencies, we consider a robot arm that moves a baby mobile toy to get visual reward. First, the robot explores the continuous sensorimotor space by associating visual stimuli to motor actions through motor babbling. After exploration, the robot uses the experience from its memory and exploits it, thus optimizing its motion to perceive more visual stimuli. The proposed approach uses Dynamic Field Theory and is integrated in the GummiArm, a 3D printed humanoid robot arm. The results indicate a higher visual neural activation after motion learning and show the benefits of an embodied babbling strategy.

IEEE Transactions on Cognitive and Developmental Systems

According to the sensorimotor approach, perception is a form of embodied know-how, constituted by lawful regularities in the sensorimotor flow or in sensorimotor contingencies (SMCs) in an active and situated agent. Despite the attention that this approach has attracted, there have been few attempts to define its core concepts formally. In this paper, we examine the idea of SMCs and argue that its use involves notions that need to be distinguished. We introduce four distinct kinds of SMCs, which we define operationally.These are the notions of sensorimotor environment (open-loop motor-induced sensory variations), sensorimotor habitat (closed-loop sensorimotor trajectories), sensorimotor coordination (reliable sensorimotor patterns playing a functional role), and sensorimotor strategy (normative organization of sensorimotor coordinations). We make use of a minimal dynamical model of visually guided categorization to test the explanatory value of the different kinds of SMCs. Finally, we discuss the impact of our definitions on the conceptual development and empirical as well as model-based testing of the claims of the sensorimotor approach.

Intellectica. Revue de l'Association pour la Recherche Cognitive, 2002

Sensory systems are associated with motor systems for perception. In the absence of motor control over the orientation of the sensory input, a person may have no idea from where the information is coming, and thus no ability to locate it in space. Sensory substitution studies have demonstrated that the sensory part of a sensory-motor loop can be provided by artificial receptors leading to a brain-machine interface (BMI). We now propose that the motor component of the sensory-motor coupling can be replaced by a "virtual" movement. We suggest that it is possible to progress to the point where predictable movement, not observed except for some sign of its initiation, could be imagined and by that means the mental image of movement could substitute for the motor component of the loop. We further suggest that, due to the much faster information transmission of the skin than the eye, innovative information presentation, such as fast sequencing and time division multiplexing can be used to partially compensate for the relatively small number of tactile stimulus points in the BMI. With such a system, incorporating humans-inthe-loop for industrial applications could result in increased efficiency and humanization of tasks that presently are highly stressful.

frontiers in neurorobotics, 2017

In the context of the dynamical system approach to cognition and supposing that brains or brain-like systems controlling the behavior of autonomous systems are permanently driven by their sensor signals, the paper approaches the question of neurodynamics in the sensorimotor loop in a purely formal way. This is carefully done by addressing the problem in three steps, using the time-discrete dynamics of standard neural networks and a fiber space representation for better clearness. Furthermore, concepts like meta-transients, parametric stability and dynamical forms are introduced, where meta-transients describe the effect of realistic sensor inputs, parametric stability refers to a class of sensor inputs all generating the "same type" of dynamic behavior, and a dynamical form comprises the corresponding class of parametrized dynamical systems. It is argued that dynamical forms are the essential internal representatives of behavior relevant external situations. Consequently, it is suggested that dynamical forms are the basis for a memory of these situations. Finally, based on the observation that not all brain process have a direct effect on the motor activity, a natural splitting of neurodynamics into vertical (internal) and horizontal (effective) parts is introduced.

Neural Networks, 1999

We present an architecture to generate behavior for an anthropomorphic robot. The goal is to equip the robot with the capacity to interact with a human. Motivated by the research on biological systems, our basic assumption is that the behavior to perform determines the external and internal structure of the behaving system. We describe the anthropomorphic design of our robot and present a distributed control system that generates human-like navigation and manipulation behavior. As the mathematical framework for this purpose we have developed a control system which is entirely based on dynamical systems in the form of instantiated dynamics and neural fields. We also present a dynamic scheme for behavioral organization based on competitive dynamics.

IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews), 2000

Both in designing teleoperators or haptic interfaces and in fundamental biological motor control studies, it is important to characterize the motor commands and mechanical impedance responses of the operator (or subject). Although such a characterization is fundamentally impossible for isolated movements when these two aspects of motor behaviour have similar time scales (as is the case with humans), it is nonetheless possible, if we are dealing with repeated movements, to measure a trajectory which is analogous to the current source in Norton-equivalent electrical circuits. We define the attractor trajectory to be this equivalent source and show that it rigorously embodies the notion of the attractor point of a time-evolving system. We demonstrate that most previous attempts to test a controversial motor control hypothesis known as the equilibrium point or virtual trajectory hypothesis are based on inadequate models of the neuromuscular system and we propose here a model-independent means of testing the hypothesis based on a comparison of measurable attractor trajectories at different levels of the motor system. We present and demonstrate means of making such measurements experimentally and of assigning error bounds to the estimated trajectories.

Frontiers in psychology, 2015

2018

Robots in human facing environments will move alongside human beings. This movement has both functional and expressive meaning and plays a crucial role in human perception of robots. Secondarily, how the robot is controlled – through methods like movement or programming and drivers like oneself or an algorithm – factors into human perceptions. This paper outlines the use of an embodied movement installation, “The Loop”, to understand perceptions generated between humans and various technological agents, including a NAO robot and a virtual avatar. Participants were questioned about their perceptions of control in the various agents. Initial results with human subjects demonstrate an increased likelihood to rate a robot and a robotic shadow as algorithmically controlled, versus a human performer and a human-shaped VR avatar which were more likely rated as human actor controlled or split between algorithm/human actor. Participants also showed a tendency to rate their own performance in...

New Ideas in Psychology, 2013