Adaptive visual servoing for various kinds of robot systems

Hosoda, Koh; Asada, Minoru

doi:10.1007/bfb0112991

Cited by 6 publications

(5 citation statements)

References 23 publications

(51 reference statements)

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“…Perceptual systems have been integrated in various ways with behavior. Vision sensors, for example, have been combined with a control system to detect obstacles and generate context-appropriate robot behavior [21]. However, most of the locomotion and perceptional systems were developed separately: a self-contained perception mechanism handles obstacle avoidance and its output-a movement plan-is used as input for the locomotion mechanism.…”

Section: Perception and Motion Integrationmentioning

confidence: 99%

Neuro-Cognitive Locomotion with Dynamic Attention on Topological Structure

2023

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This paper discusses a mechanism for integrating locomotion with cognition in robots. We demonstrate an attentional ability model that can dynamically change the focus of its perceptual area by integrating attention and perception to generate behavior. The proposed model considers both internal sensory information and also external sensory information. We also propose affordance detection that identifies different actions depending on the robot’s immediate possibilities. Attention is represented in a topological structure generated by a growing neural gas that uses 3D point-cloud data. When the robot faces an obstacle, the topological map density increases in the suspected obstacle area. From here, affordance information is processed directly into the behavior pattern generator, which comprises interconnections between motor and internal sensory neurons. The attention model increases the density associated with the suspected obstacle to produce a detailed representation of the obstacle. Then, the robot processes the cognitive information to enact a short-term adaptation to its locomotion by changing its swing pattern or movement plan. To test the effectiveness of the proposed model, it is implemented in a computer simulation and also in a medium-sized, four-legged robot. The experiments validate the advantages in three categories: (1) Development of attention model using topological structure, (2) Integration between attention and affordance in moving behavior, (3) Integration of exteroceptive sensory information to lower-level control of locomotion generator.

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Section: Perception and Motion Integrationmentioning

confidence: 99%

Neuro-Cognitive Locomotion with Dynamic Attention on Topological Structure

2023

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“…Nonetheless, some researchers have developed methods for integrating the perceptual system and the behavioral system. Some have generated appropriate robot behavior using a vision sensor combined with a control system to detect obstacles 4 . However, most locomotion and perceptional systems have been developed separately, building a perception model for obstacle avoidance and using its output (movement plan) as the input for the locomotion model; nonetheless, the approach has been implemented in a legged robot 5 , 6 .…”

Section: Introductionmentioning

confidence: 99%

Multi-scopic neuro-cognitive adaptation for legged locomotion robots

Saputra

Wada

Masuda

et al. 2022

Sci Rep

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Dynamic locomotion is realized through a simultaneous integration of adaptability and optimality. This article proposes a neuro-cognitive model for a multi-legged locomotion robot that can seamlessly integrate multi-modal sensing, ecological perception, and cognition through the coordination of interoceptive and exteroceptive sensory information. Importantly, cognitive models can be discussed as micro-, meso-, and macro-scopic; these concepts correspond to sensing, perception, and cognition; and short-, medium-, and long-term adaptation (in terms of ecological psychology). The proposed neuro-cognitive model integrates these intelligent functions from a multi-scopic point of view. Macroscopic-level presents an attention mechanism with short-term adaptive locomotion control conducted by a lower-level sensorimotor coordination-based model. Macrosopic-level serves environmental cognitive map featuring higher-level behavior planning. Mesoscopic level shows integration between the microscopic and macroscopic approaches, enabling the model to reconstruct a map and conduct localization using bottom-up facial environmental information and top-down map information, generating intention towards the ultimate goal at the macroscopic level. The experiments demonstrated that adaptability and optimality of multi-legged locomotion could be achieved using the proposed multi-scale neuro-cognitive model, from short to long-term adaptation, with efficient computational usage. Future research directions can be implemented not only in robotics contexts but also in the context of interdisciplinary studies incorporating cognitive science and ecological psychology.

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Section: Introductionmentioning

confidence: 99%

Multi-Scopic Neuro-Cognitive Adaptation for Legged Locomotion Robots

Saputra

Wada

Masuda

et al. 2021

Preprint

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Dynamic locomotion is realized through a simultaneous integration of adaptability and optimality. This article proposes a neuro-cognitive model for multi-legged locomotion robot that can seamlessly integrate multi-modal sensing, ecological perception, and cognition through the coordination of interoceptive and exteroceptive sensory information. Importantly, cognitive models can be discussed as micro-, meso-, and macro-scopic; these concepts correspond to sensing, perception, and cognition; and short-, medium-, and long-term adaptation (in terms of ecological psychology). The proposed neuro-cognitive model integrates these intelligent functions from a multi-scopic point of view. Macroscopic-level presents an attention mechanism with short-term adaptive locomotion control conducted by lower-level sensorimotor coordination-based model. Macrosopic-level serves environmental cognitive map featuring higher-level behavior planning. Mesoscopic level shows integration between the microscopic and macroscopic approaches, enabling the model to reconstruct a map and conduct localization using bottom-up facial environmental information and top-down map information, generating intention towards the ultimate goal at the macroscopic level. The experiments demonstrated that adaptability and optimality of multi-legged locomotion could be achieved using the proposed multi-scale neuro-cognitive model, from short to long-term adaptation, with efficient computational usage. Future research directions can be implemented not only in robotics contexts but also in the context of interdisciplinary studies incorporating cognitive science and ecological psychology.

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Adaptive visual servoing for various kinds of robot systems

Cited by 6 publications

References 23 publications

Neuro-Cognitive Locomotion with Dynamic Attention on Topological Structure

Neuro-Cognitive Locomotion with Dynamic Attention on Topological Structure

Multi-scopic neuro-cognitive adaptation for legged locomotion robots

Multi-Scopic Neuro-Cognitive Adaptation for Legged Locomotion Robots

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