Study on a Modular and Reconfigurable Robot That Can Be Used in Natural Disaster Events

This paper presents a modular reconfigurable robotic system for search-and-rescue operations in natural catastrophe scenarios, addressing the structural rigidity, limited energy autonomy, and restricted victim-support capabilities of conventional rescue robots. The contributions are organized into four dimensions. First, a modular mechanical architecture is proposed in which modules operate independently or are interconnected through a multifunctional flexible tube providing mechanical coupling, shielded communication, wireless power transfer, and transport of vital supplies; a two-degree-of-freedom leg module enables star-, snake-, worm-, and chain-like configurations. Second, a unified locomotion model for both wheeled and legged configurations is developed through an equivalent-radius formulation, and stability is analyzed using the Zero-Moment Point (ZMP) criterion and the Linear Inverted Pendulum Model (LIPM). Third, a linear control law is formulated to compensate for longitudinal, lateral-slip, and orientation errors, while module coordination is achieved through a de-centralized, fault-tolerant status-message protocol. Fourth, three proof-of-concept prototype versions of modular reconfigurable robots with servo-driven active interconnections were manufactured by additive technologies. For Version 3, a Virtual Reality workflow integrating SolidWorks (version SOLIDWORKS 2023), Blender (version Blender 4.4.3, Unreal Engine 5 version 5.8), and Unreal Engine 5, with full-body inverse kinematics and physics-based simulation, was used to evaluate sensor-driven motion and obstacle avoidance. The results demonstrate the feasibility of a scalable platform able to adapt its locomotion and functional configuration to post-disaster environments

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Publication Details

Journal
Applied Sciences
Published
2026-11-03
DOI
https://doi.org/10.3390/app162110915
Primary Topic
Modular Robots and Swarm Intelligence
Type
article
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article

Study on a Modular and Reconfigurable Robot That Can Be Used in Natural Disaster Events

Robert Ciobanu, Andreea Dana Alionte, Cristian Gabriel Alionte, Lucian Bogatu et al.
Applied Sciences
Modular Robots and Swarm Intelligence
article

Study on a Modular and Reconfigurable Robot That Can Be Used in Natural Disaster Events

Robert Ciobanu, Andreea Dana Alionte, Cristian Gabriel Alionte, Lucian Bogatu, Vlad-Andrei Stănescu, Marius-Valentin Gheorghe
article en

Abstract

This paper presents a modular reconfigurable robotic system for search-and-rescue operations in natural catastrophe scenarios, addressing the structural rigidity, limited energy autonomy, and restricted victim-support capabilities of conventional rescue robots. The contributions are organized into four dimensions. First, a modular mechanical architecture is proposed in which modules operate independently or are interconnected through a multifunctional flexible tube providing mechanical coupling, shielded communication, wireless power transfer, and transport of vital supplies; a two-degree-of-freedom leg module enables star-, snake-, worm-, and chain-like configurations. Second, a unified locomotion model for both wheeled and legged configurations is developed through an equivalent-radius formulation, and stability is analyzed using the Zero-Moment Point (ZMP) criterion and the Linear Inverted Pendulum Model (LIPM). Third, a linear control law is formulated to compensate for longitudinal, lateral-slip, and orientation errors, while module coordination is achieved through a de-centralized, fault-tolerant status-message protocol. Fourth, three proof-of-concept prototype versions of modular reconfigurable robots with servo-driven active interconnections were manufactured by additive technologies. For Version 3, a Virtual Reality workflow integrating SolidWorks (version SOLIDWORKS 2023), Blender (version Blender 4.4.3, Unreal Engine 5 version 5.8), and Unreal Engine 5, with full-body inverse kinematics and physics-based simulation, was used to evaluate sensor-driven motion and obstacle avoidance. The results demonstrate the feasibility of a scalable platform able to adapt its locomotion and functional configuration to post-disaster environments

Applied SciencesVol. 16(21)
Universitatea Națională de Știință și Tehnologie Politehnica București (RO)
Openalex Percentile: Top 24%
Modular Robots and Swarm Intelligence
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