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Daniel Giełdowski

Publications and source records attributed to Daniel Giełdowski.

5 recordsLinked to original sources

ROS-related Robotic Systems Development with V-model-based Application of MeROS Metamodel

Systems built on the Robot Operating System (ROS) are increasingly easy to assemble, yet hard to govern and reliably coordinate. Beyond the sheer number of subsystems involved, the difficulty stems from their diversity and interaction depth. In this paper, we use a compact heterogeneous robotic system (HeROS), combining mobile and manipulation capabilities, as a demonstration vehicle under dynamically changing tasks. Notably, all its subsystems are powered by ROS. The use of compatible interfaces and other ROS integration capabilities simplifies the construction of such systems. However, this only addresses part of the complexity: the semantic coherence and structural traceability are even more important for precise coordination and call for deliberate engineering methods. The Model-Based Systems Engineering (MBSE) discipline, which emerged from the experience of complexity management in large-scale engineering domains, offers the methodological foundations needed. Despite their strengths in complementary aspects of robotics systems engineering, the lack of a unified approach to integrate ROS and MBSE hinders the full potential of these tools. Motivated by the anticipated impact of such a synergy in robotics practice, we propose a structured methodology based on MeROS - a SysML metamodel created specifically to put the ROS-based systems into the focus of the MBSE workflow. As its methodological backbone, we adapt the well-known V-model to this context, illustrating how complex robotic systems can be designed with traceability and validation capabilities embedded into their lifecycle using practices familiar to engineering teams.

cs.RO↗

TaBSA -- A framework for training and benchmarking algorithms scheduling tasks for mobile robots working in dynamic environments

This article introduces a software framework for benchmarking robot task scheduling algorithms in dynamic and uncertain service environments. The system provides standardized interfaces, configurable scenarios with movable objects, human agents, tools for automated test generation, and performance evaluation. It supports both classical and AI-based methods, enabling repeatable, comparable assessments across diverse tasks and configurations. The framework facilitates diagnosis of algorithm behavior, identification of implementation flaws, and selection or tuning of strategies for specific applications. It includes a SysML-based domain-specific language for structured scenario modeling and integrates with the ROS-based system for runtime execution. Validated on patrol, fall assistance, and pick-and-place tasks, the open-source framework is suited for researchers and integrators developing and testing scheduling algorithms under real-world-inspired conditions.

cs.RO↗

HeROS: a miniaturised platform for research and development on Heterogeneous RObotic Systems

Tests and prototyping are vital in the research and development of robotic systems. Work with target hardware is problematic. Hence, in the article, a low-cost, miniaturised physical platform is presented to deal with experiments on heterogeneous robotic systems. The platform comprises a physical board with tiles of the standardised base, diverse mobile robots, and manipulation robots. The number of exemplary applications validates the usefulness of the solution.

cs.RO↗

A comparative analysis of deep learning models for lung segmentation on X-ray images

Robust and highly accurate lung segmentation in X-rays is crucial in medical imaging. This study evaluates deep learning solutions for this task, ranking existing methods and analyzing their performance under diverse image modifications. Out of 61 analyzed papers, only nine offered implementation or pre-trained models, enabling assessment of three prominent methods: Lung VAE, TransResUNet, and CE-Net. The analysis revealed that CE-Net performs best, demonstrating the highest values in dice similarity coefficient and intersection over union metric.

eess.IV↗

An intent-based approach for creating assistive robots' control systems

The current research standards in robotics demand general approaches to robots' controllers development. In the assistive robotics domain, the human-machine interaction plays a substantial role. Especially, the humans generate intents that affect robot control system. In the article an approach is presented for creating control systems for assistive robots, which reacts to users' intents delivered by voice commands, buttons, or an operator console. The whole approach was applied to the real system consisting of customised TIAGo robot and additional hardware components. The exemplary experiments performed on the platform illustrate the motivation for diversification of human-machine interfaces in assistive robots.

cs.RO↗