Footprint Reduction of Sensor Control Modules for Remote Portable Laboratories
Sebastian-Alexandru Arghirescu1, Maria Drăgan1, Octavian Fratu2
1Campus Centre, University "Politehnica" of Bucharest, 061102 Bucharest, Romania.
This study presents a microcontroller-based mobile laboratory control system to enhance robotic environmental monitoring. The adaptable design reduces space requirements, improving robot efficiency for pollution analysis.
Area of Science:
- Environmental Science
- Robotics
- Sensor Technology
Background:
- Increasing automation in environmental monitoring necessitates greater autonomy for field robots.
- Robot payload capacity is a critical factor for comprehensive environmental analysis, requiring a balance between lab size, weight, complexity, and robot autonomy.
- Current technology limitations in autonomous battery charging cycles further emphasize the need for efficient mobile laboratory designs.
Purpose of the Study:
- To develop a microcontroller-based architecture for a mobile laboratory control system.
- To design a system adaptable for both aerial and aquatic mobile robotic platforms.
- To reduce the physical footprint of mobile laboratories for enhanced robotic deployment.
Main Methods:
- Development of a microcontroller-based control system architecture.
- Design for integration onto aerial and aquatic mobile robotic vectors.
- Evaluation of system adaptability for diverse sensor types and configurations.
Main Results:
- The proposed microcontroller-based system architecture is adaptable for various sensor configurations.
- The system significantly reduces the space required compared to existing embedded products.
- The design is suitable for deployment on both aerial and aquatic mobile platforms.
Conclusions:
- A versatile and compact mobile laboratory control system can be achieved using a microcontroller-based architecture.
- This approach offers a scalable solution for environmental monitoring robots, improving payload efficiency.
- The system's adaptability supports diverse sensing needs in pollution monitoring across different environments.
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