Revisiting active perception

Bajcsy, Růžena; Aloimonos, Yiannis; Tsotsos, John K.

doi:10.1007/s10514-017-9615-3

Cited by 255 publications

(170 citation statements)

References 111 publications

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“…Second, there is an explicitly active component in perceptual processing, in that the agent selects the next action (partly) for perceptual and epistemic reasons, e.g., to disambiguate amongst perceptual hypotheses, to keep the stimulus constant or de-noise it, etc. (see also [33]). …”

Section: Active Perception From a Model-based Perspectivementioning

confidence: 85%

“…In sum, these theories (and others, see [33] for a review) emphasize the key features of an interactive view of perception and, most prominently, the mutual dependency between perception on action. We have mentioned above one core idea of the ecological approach to perception-that living organisms are informationally coupled to the environment and do not need to represent this information internally [12].…”

Section: A Critique Of Passive Perceptionmentioning

confidence: 96%

“…In this perspective, an action or a sequence of actions such as a grasp performed with the whole hand (power grasp) would play the (active) role of an "experiment" that updates the beliefs about the alternative hypotheses; and the experiment can be constructed in such a way that it (for example) disambiguates the alternative hypotheses in the best way [33]. Hence, belief updating would not stem from passively collecting motor-sensory statistics, but from a more active, hypothesis testing process-which constitutes an action-based metaphor for saccadic control [35,36] and haptic exploration [37].…”

Section: Active Perception From a Model-based Perspectivementioning

confidence: 99%

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Model-Based Approaches to Active Perception and Control

Pezzulo

Rigoli

Iodice

et al. 2017

Entropy

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Abstract:There is an on-going debate in cognitive (neuro) science and philosophy between classical cognitive theory and embodied, embedded, extended, and enactive ("4-Es") views of cognition-a family of theories that emphasize the role of the body in cognition and the importance of brain-body-environment interaction over and above internal representation. This debate touches foundational issues, such as whether the brain internally represents the external environment, and "infers" or "computes" something. Here we focus on two (4-Es-based) criticisms to traditional cognitive theories-to the notions of passive perception and of serial information processing-and discuss alternative ways to address them, by appealing to frameworks that use, or do not use, notions of internal modelling and inference. Our analysis illustrates that: an explicitly inferential framework can capture some key aspects of embodied and enactive theories of cognition; some claims of computational and dynamical theories can be reconciled rather than seen as alternative explanations of cognitive phenomena; and some aspects of cognitive processing (e.g., detached cognitive operations, such as planning and imagination) that are sometimes puzzling to explain from enactive and non-representational perspectives can, instead, be captured nicely from the perspective that internal generative models and predictive processing mediate adaptive control loops.

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Section: Active Perception From a Model-based Perspectivementioning

confidence: 85%

Section: A Critique Of Passive Perceptionmentioning

confidence: 96%

Section: Active Perception From a Model-based Perspectivementioning

confidence: 99%

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Model-Based Approaches to Active Perception and Control

Pezzulo

Rigoli

Iodice

et al. 2017

Entropy

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“…In biological active vision, during the visual exploration of the 3D environment, an accurate eye posture on the object of interest is usually obtained by saccades followed by a vergence refinement (Enright 1998;Rea et al 2014;Bajcsy et al 2016). From this perspective, we implemented a control strategy composed of a sequence of two movements.…”

Section: Integrated Vergence and Version Controlmentioning

confidence: 99%

“…From the very beginning to nowadays, the perceptual process of an active vision system is considered to be an "exploratory and searching" activity (Aloimonos et al 1988;Bajcsy et al 2016) in which the system modifies the cameras' viewpoints in order to exploit its full potential.…”

Section: Introductionmentioning

confidence: 99%

A Portable Bio-Inspired Architecture for Efficient Robotic Vergence Control

et al. 2016

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In stereoscopic vision, the ability of perceiving the three-dimensional structure of the surrounding environment is subordinated to a precise and effective motor control for the binocular coordination of the eyes/cameras. If, on the one side, the binocular coordination of camera movements is a complicating factor, on the other side, a proper vergence control, acting on the binocular disparity, facilitates the binocular fusion and the subsequent stereoscopic perception process. In real-world situations, an effective vergence control requires further features other than real time capabilities: real robot systems are indeed characterized by mechanical and geometrical imprecision that affect the binocular vision, and the illumination conditions are changeable and unpredictable. Moreover, in order to allow an effective visual exploration of the peripersonal space, it is necessary to cope with different gaze directions and provide a large working space. The proposed control strategy resorts to a neuromimetic approach that provides a distributed representation of disparity information. trol, which directly interacts with saccadic control. Before saccade, the open-loop component is computed in correspondence of the saccade target region, to obtain a vergence correction to be applied simultaneously with the saccade. At fixation, the closed-loop component drives the binocular disparity to zero in a foveal region. The obtained vergence servos are able to actively drive both the horizontal and the vertical alignment of the optical axes on the object of interest, thus ensuring a correct vergence posture. Experimental tests were purposely designed to measure the performance of the control in the peripersonal space, and were performed on three different robot platforms. The results demonstrated that the proposed approach yields real-time and effective vergence camera movements on a visual stimulus in a wide working range, regardless of the illumination in the environment and the geometry of the system.

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Skin‐Inspired Multi‐Modal Mechanoreceptors for Dynamic Haptic Exploration

Su,

Zhang,

et al. 2024

Advanced Materials

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Active sensing is a fundamental aspect of human and animal interactions with the environment, providing essential information about the hardness, texture, and tackiness of objects. This ability stems from the presence of diverse mechanoreceptors in our skin, capable of detecting a wide range of stimuli and from the sensorimotor control of biological mechanism. In contrast, existing tactile sensors for robotic applications typically excel in identifying only limited types of information, lacking the versatility of biological mechanoreceptors and the requisite sensing strategies to extract tactile information proactively. Here, inspired by human haptic perception, we develop a skin‐inspired artificial 3D mechanoreceptor (SENS) capable of detecting multiple mechanical stimuli to bridge sensing and action in a closed‐loop sensorimotor system for dynamic haptic exploration. A tensor‐based non‐linear theoretical model is established to characterize the 3D deformation (e.g., tensile, compressive and shear deformation) of SENS, providing guidance for the design and optimization of multimode sensing properties with high fidelity. Based on SENS, we further demonstrate a closed‐loop robotic system capable of recognizing objects with improved accuracy (∼96%). This dynamic haptic exploration approach shows promise for a wide range of applications such as autonomous learning, healthcare, and space and deep‐sea exploration.This article is protected by copyright. All rights reserved

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Revisiting active perception

Cited by 255 publications

References 111 publications

Model-Based Approaches to Active Perception and Control

Model-Based Approaches to Active Perception and Control

A Portable Bio-Inspired Architecture for Efficient Robotic Vergence Control

Skin‐Inspired Multi‐Modal Mechanoreceptors for Dynamic Haptic Exploration

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