What Is Morphological Computation? On How the Body Contributes to Cognition and Control

Müller, Vincent C.; Hoffmann, Matej

doi:10.1162/artl_a_00219

Cited by 138 publications

(144 citation statements)

References 69 publications

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“…The attractors self-stabilizing in the sensorimotor loop may then give rise to complex patterns of regular and of chaotic motion primitives [15], which can be selected in a second step using 'kick control' [16]. From a general perspective, kick control is an instance of a higher-level control mechanism exploiting the reduction in control complexity provided by morphologically computing robots [17,18]. These approaches are hence different from other works where closed-loop policies are applied on the top of open-loop gait cycles [19,20].…”

Section: Introductionmentioning

confidence: 99%

When the goal is to generate a series of activities: A self-organized simulated robot arm

2019

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Behavior is characterized by sequences of goal oriented conducts, such as food uptake, socializing and resting. Classically, one would define for each task a corresponding satisfaction level, with the agent engaging, at a given time, in the activity having the lowest satisfaction level. Alternatively, one may consider that the agent follows the overarching objective to generate sequences of distinct activities. To achieve a balanced distribution of activities would then be the primary goal, and not to master a specific task. In this setting the agent would show two types of behaviors, task-oriented and task-searching phases, with the latter interseeding the former. We study the emergence of autonomous task switching for the case of a simulated robot arm. Grasping one of several moving objects corresponds in this setting to a specific activity. Overall, the arm should follow a given object temporarily and then move away, in order to search for a new target and reengage. We show that this behavior can be generated robustly when modeling the arm as an adaptive dynamical system. The dissipation function is in this approach time dependent. The arm is in a dissipative state when searching for a nearby object, dissipating energy on approach. Once close, the dissipation function starts to increase, with the eventual sign change implying that the arm will take up energy and wander off. The resulting explorative state ends when the dissipation function becomes again negative and the arm selects a new target. We believe that our approach may be generalized to generate self-organized sequences of activities in general.

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Section: Introductionmentioning

confidence: 99%

When the goal is to generate a series of activities: A self-organized simulated robot arm

2019

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“…Instead of discussing the resemblance of robot bodies to human bodies in the spirit of the so-called 'Uncanny Valley' (Destephe et al 2015;Mori 1970), we focus on a 'hybrid robot body' that can exhibit a collection of emotionally appealing human-like traits like blinking eyes, speech and culturally coded dance movements and non-human traits like plastic coverage, three finger hands and a slow, stiff, robot-like way of walking. In the field of engineering studies, robot bodies are approached from the perspectives of morphological computation and robot morphology in order to consider their resemblance to different types of biological bodies with human or non-human traits (e.g., Hoffmann and Müller 2017). More specifically, morphological computation is a concept used in robot engineering to examine physical bodies in the context of robotics as a means of carrying out computations considered relevant to their successful interaction with the environment (Hauser and Corucci 2017).…”

Section: Introductionmentioning

confidence: 99%

Motions with Emotions?

Parviainen¹,

Aerschot²,

Särkikoski³

et al. 2019

Techné: Research in Philosophy and Technology

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This article examines how the interactive capabilities of companion robots, particularly their materiality and animate movements, appeal to human users and generate an image of aliveness. Building on Husserl's phenomenological notion of a 'double body' and theories of emotions as affective responses, we develop a new understanding of the robots' simulated aliveness. Analyzing empirical findings of a field study on the use of the robot Zora in care homes for older people, we suggest that the aliveness of companion robots is the result of a combination of four aspects: 1) material ingredients, 2) morphology, 3) animate movements guided by software programs and human operators as in Wizard of Oz-settings and 4) anthropomorphising narratives created by their users to support the robot's performance. We suggest that narratives on affective states, such as, sleepiness or becoming frightened attached to the robot trigger users' empathic feelings, caring and tenderness toward the robot.

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“…Nonetheless, the concept of morphological computation does not have a clear definition as discussed in Müller and Hoffmann (2016). In Füchslin et al (2013), the authors refer to the first International Conference on Morphological Computation in Venice in 2007, where it was defined as “any process that serves a computational purpose, has clearly assignable input and output states, is programmable (i.e., the behavior can be adapted by varying a set of parameters) and has a sort of teleological embedding.” This definition is however rather broad as it also includes every traditional digital computing means.…”

Section: Introductionmentioning

confidence: 99%

Morphological Properties of Mass–Spring Networks for Optimal Locomotion Learning

et al. 2017

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Robots have proven very useful in automating industrial processes. Their rigid components and powerful actuators, however, render them unsafe or unfit to work in normal human environments such as schools or hospitals. Robots made of compliant, softer materials may offer a valid alternative. Yet, the dynamics of these compliant robots are much more complicated compared to normal rigid robots of which all components can be accurately controlled. It is often claimed that, by using the concept of morphological computation, the dynamical complexity can become a strength. On the one hand, the use of flexible materials can lead to higher power efficiency and more fluent and robust motions. On the other hand, using embodiment in a closed-loop controller, part of the control task itself can be outsourced to the body dynamics. This can significantly simplify the additional resources required for locomotion control. To this goal, a first step consists in an exploration of the trade-offs between morphology, efficiency of locomotion, and the ability of a mechanical body to serve as a computational resource. In this work, we use a detailed dynamical model of a Mass–Spring–Damper (MSD) network to study these trade-offs. We first investigate the influence of the network size and compliance on locomotion quality and energy efficiency by optimizing an external open-loop controller using evolutionary algorithms. We find that larger networks can lead to more stable gaits and that the system’s optimal compliance to maximize the traveled distance is directly linked to the desired frequency of locomotion. In the last set of experiments, the suitability of MSD bodies for being used in a closed loop is also investigated. Since maximally efficient actuator signals are clearly related to the natural body dynamics, in a sense, the body is tailored for the task of contributing to its own control. Using the same simulation platform, we therefore study how the network states can be successfully used to create a feedback signal and how its accuracy is linked to the body size.

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What Is Morphological Computation? On How the Body Contributes to Cognition and Control

Cited by 138 publications

References 69 publications

When the goal is to generate a series of activities: A self-organized simulated robot arm

When the goal is to generate a series of activities: A self-organized simulated robot arm

Motions with Emotions?

Morphological Properties of Mass–Spring Networks for Optimal Locomotion Learning

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