Neuro-Activity-Based Dynamic Path Planner for 3-D Rough Terrain

Saputra, Azhar Aulia; Toda, Yuichiro; Botzheim, János; Kubota, Naoyuki

doi:10.1109/tcds.2017.2711013

Cited by 12 publications

(4 citation statements)

References 44 publications

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“…Macroscopically, we focused on designing higher-level processing that can enable motion planning, behavior generation, and knowledge building. This led to the development of two modules: (1) cognitive map (CM) module using topological-structure-based map reconstruction and (2) neural based path planning (PP) (see previous research 40 ) module based on the map constructed. The CM module was developed through higher-level behavior planning based on the collection or memory of large-scale SI.…”

Section: Discussionmentioning

confidence: 99%

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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: Discussionmentioning

confidence: 99%

“…When the robot encounters an unpredictable collision, the path planner dynamically changes the pathway. The PP module has been explained in our previous publication 40 .…”

Section: Methodsmentioning

confidence: 99%

Multi-scopic neuro-cognitive adaptation for legged locomotion robots

Saputra

Wada

Masuda

et al. 2022

Sci Rep

Self Cite

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“…The aim of this model is to reduce the data representation overhead associated with the 3D point-cloud data. The basic real-time Growing Neural Gas (GNG) technique has been implemented in our previous path planning model (Saputra et al, 2017). We extended the GNG by adding a dynamic-density model.…”

Section: Dynamic-density Topological Map-building With Attention Modelmentioning

confidence: 99%

AQuRo: A Cat-like Adaptive Quadruped Robot With Novel Bio-Inspired Capabilities

et al. 2021

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There are currently many quadruped robots suited to a wide range of applications, but traversing some terrains, such as vertical ladders, remains an open challenge. There is still a need to develop adaptive robots that can walk and climb efficiently. This paper presents an adaptive quadruped robot that, by mimicking feline structure, supports several novel capabilities. We design a novel paw structure and several point-cloud-based sensory structures incorporating a quad-composite time-of-flight sensor and a dual-laser range finder. The proposed robot is equipped with physical and cognitive capabilities which include: 1) a dynamic-density topological map building with attention model, 2) affordance perception using the topological map, and 3) a neural-based locomotion model. The novel capabilities show strong integration between locomotion and internal–external sensory information, enabling short-term adaptations in response to environmental changes. The robot performed well in several situations: walking on natural terrain, walking with a leg malfunction, avoiding a sudden obstacle, climbing a vertical ladder. Further, we consider current problems and future development.

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“…When the robot encounters an unpredictable collision, the path planner dynamically changes the pathway. The PP module has been explained in our previous publication 36 .…”

Section: Macroscopic Neuro-cognitive Adaptationmentioning

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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Neuro-Activity-Based Dynamic Path Planner for 3-D Rough Terrain

Cited by 12 publications

References 44 publications

Multi-scopic neuro-cognitive adaptation for legged locomotion robots

Multi-scopic neuro-cognitive adaptation for legged locomotion robots

AQuRo: A Cat-like Adaptive Quadruped Robot With Novel Bio-Inspired Capabilities

Multi-Scopic Neuro-Cognitive Adaptation for Legged Locomotion Robots

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