KANT: A Tool for Grounding and Knowledge Management

González-Santamarta, Miguel Á.; Rodríguez-Lera, Francisco J.; Martı́n, Francisco; Fernández-Llamas, Camino; Olivera, Vicente Matellán

doi:10.1007/978-3-031-06527-9_45

Cited by 4 publications

(1 citation statement)

References 9 publications

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“…• Symbolic Layer: this layer is composed of the knowledge base where the symbolic knowledge is stored. It is implemented using the knowledge base presented in (González-Santamarta et al 2022). As a result, the knowledge base can be ROS 2 node or MongoDB.…”

Section: Sailor Pipelinementioning

confidence: 99%

SAILOR: Perceptual Anchoring For Robotic Cognitive Architectures

González-Santamarta¹,

Rodríguez-Lera²,

Olivera³

2023

Preprint

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Symbolic anchoring is a crucial problem in the field of robotics, as it enables robots to obtain symbolic knowledge from the perceptual information acquired through their sensors. In cognitive-based robots, this process of processing sub-symbolic data from real-world sensors to obtain symbolic knowledge is still an open problem. To address this issue, this paper presents SAILOR, a framework for providing symbolic anchoring in ROS 2 ecosystem. SAILOR aims to maintain the link between symbolic data and perceptual data in real robots over time. It provides a semantic world modeling approach using two deep learning-based sub-symbolic robotic skills: object recognition and matching function. The object recognition skill allows the robot to recognize and identify objects in its environment, while the matching function enables the robot to decide if new perceptual data corresponds to existing symbolic data. This paper provides a description of the framework, the pipeline and development as well as its integration in MERLIN2, a hybrid cognitive architecture fully functional in robots running ROS 2.

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Section: Sailor Pipelinementioning

confidence: 99%

SAILOR: Perceptual Anchoring For Robotic Cognitive Architectures

González-Santamarta¹,

Rodríguez-Lera²,

Olivera³

2023

Preprint

View full text Add to dashboard Cite

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YASMIN: Yet Another State MachINe

González-Santamarta

Rodríguez-Lera

Matellán-Olivera

et al. 2022

ROBOT2022: Fifth Iberian Robotics Conference

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A Hybrid Cognitive Architecture to Generate, Control, Plan, and Monitor Behaviors for Interactive Autonomous Robots

González-Santamarta,

Rodríguez-Lera,

Fernández-Llamas

et al. 2024

Int J of Soc Robotics

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Interactive robots not only need to react in predefined or deterministic scenarios but also learn and adapt in real-time, mirroring cognitive flexibility akin to human intelligence. Achieving this autonomy entails developing cognitive architectures that integrate reactive, deliberative and emergent capabilities. Thus, this paper presents MERLIN2, a hybrid cognitive architecture to generate, control, plan, and monitor behaviors in autonomous robots. This architecture combines reactive, deliberative, and emergent components, aiming to enhance adaptability in dynamic environments and make intelligent real-time decisions, thereby improving autonomy and performance. MERLIN2 comprises a deliberative system, based on a knowledge base and a symbolic planner; and a behavioral system composed of reactive components and several emergent components. It addresses core cognitive aspects like action selection, perception, memory, learning, reasoning, and explainability. MERLIN2 is evaluated in a simulated world and in the real world Carry My Luggage task from the RoboCup@Home. Therefore, the experimentation presented in this article showcases the architecture as a valid solution for autonomous robots.

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KANT: A Tool for Grounding and Knowledge Management

Cited by 4 publications

References 9 publications

SAILOR: Perceptual Anchoring For Robotic Cognitive Architectures

SAILOR: Perceptual Anchoring For Robotic Cognitive Architectures

YASMIN: Yet Another State MachINe

A Hybrid Cognitive Architecture to Generate, Control, Plan, and Monitor Behaviors for Interactive Autonomous Robots

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