Design of a ROS2-Based Hybrid Aerial-Ground Robot for Autonomous Inspection Applications
This study presents the design, modelling, and experimental validation of a lightweight hybrid aerial-ground robot developed for extended-duration inspection and monitoring tasks. The proposed system uniquely integrates a differential drive ground base with a quadrotor aerial module, thereby enablin...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11048919/ |
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| Summary: | This study presents the design, modelling, and experimental validation of a lightweight hybrid aerial-ground robot developed for extended-duration inspection and monitoring tasks. The proposed system uniquely integrates a differential drive ground base with a quadrotor aerial module, thereby enabling adaptive mobility that facilitates effective navigation across constrained, cluttered, and complex environments. Built upon the Robot Operating System (ROS 2) framework, the robot architecture supports real-time control, modular software integration, and distributed task execution. A distinctive feature of the presented design is its energy-efficient operational strategy, emphasizing ground-based autonomous navigation and mapping for extended endurance while selectively utilising aerial capabilities for vertical access, obstacle circumvention, and challenging terrain traversal. Comprehensive experimental evaluations have been conducted to assess the robot’s performance, confirming its capability for smooth transitions between ground and aerial modes while reliably maintaining stability, precise localisation, and robust obstacle avoidance. These results illustrate the significant potential of the developed robotic platform for autonomous deployment in applications demanding extended operation times and versatile mobility, including infrastructure inspection, environmental monitoring, and search-and-rescue missions in complex scenarios. |
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| ISSN: | 2169-3536 |