Autonomous Mobile Water Quality Measurement Robot Platform

In recent years, due to global warming and climate change, irregular localized heavy rainfall has been increasing, leading to rapid formation of closed water puddles, subsurface road areas, and zones around aging sewage pipelines throughout urban infrastructure. These water bodies serve as major breeding grounds for mosquito larvae and act as key sources of waterborne viruses and pathogenic microorganisms, posing threats to surrounding environments and public health systems. Additionally, in regions or countries lacking basic water and sewerage infrastructure rather than advanced facilities, environmental and health risks manifest with higher mortality rates in remote areas and developing countries. However, due to practical constraints in operating real-time measurement equipment to determine water resource contamination and large-scale purification facilities, there is a need for independent mobile equipment not bound to large-scale facilities that can prevent the initial spread of waterborne infectious diseases.
To remove environmental hazards in urban blind spots and facility-deficient areas, manual pest control methods have primarily been performed, with pest control personnel directly accessing sites for visual measurement and chemical spraying. However, spatio-temporal blind spots exist in areas physically inaccessible by personnel, such as overgrown streams, undersides of bridges, wetlands, or valleys, limiting intensive surveys. As an alternative, aerial pest control methods using unmanned aircraft have been attempted, but face practical limitations such as Korean aviation law regulations and high costs compared to equipment of equivalent weight. Additionally, in remote areas where infrastructure is not fully established, such as GPS-blocked areas under large bridges, shadow zones of structures, heavily forested areas, and regions with insufficient communication networks, there are practical constraints preventing drone control and operation.
The method proposed in this research involves manufacturing an autonomous mobile robot platform with mobility, and additionally equipping it with sensors and end-effectors capable of performing specialized tasks on the robot body, enabling repeated installation and expansion to perform missions according to objectives. The research aims to demonstrate the effectiveness of water quality measurement and pest control systems through autonomous mobile robots capable of independent operation via edge computing even in areas with poor infrastructure.

[Expected Effects]
Eliminating blind spots through technology
1. By having robots continuously manage riparian environments in underdeveloped areas where regular maintenance is difficult, odors, insects, and algal blooms are suppressed and prevented, providing pleasant environments.
2. Direct contact with stagnant dangerous water or entry into hazardous zones is prevented, allowing robots to perform purification work instead.
3. By providing water quality status through intuitive apps or voice guidance, personnel with low information accessibility can verify in real-time the safety of water sources and necessary work in their surroundings.
Technical aspects
1. Existing environmental management facilities and robots show high accuracy in infrastructure-dense areas, but face challenges in deep mountain puddles, countries with insufficient electrical infrastructure, and harsh terrain where environmental management personnel are difficult to deploy.
2. Through intelligent autonomous patrols and water quality measurement data processing, extensive riparian areas can be monitored 24 hours without personnel deployment.
Economic and environmental aspects
1. By detecting and purifying algal blooms, pollutants, and harmful insects at an early stage, large-scale water contamination is prevented and substantial future restoration costs are reduced.
2. Collected data is provided to local governments to establish environmental management policies based on data and facilitate budget execution.
3. Small robots perform risky and repetitive riparian purification tasks instead, eliminating the need for personnel to directly perform or deploy additional workforce.
4. For riparian areas where large corporations' water purification systems are difficult to manage, water quality measurement and purification robots made with low budgets can be deployed in large quantities to handle extensive natural environments cost-effectively and reliably obtain water quality data over wide areas.

ROS2 Jazzy 기반의 레이더 맵핑 및 전역 경로 계획을 전담하는 상위 제어기인 Raspberry Pi5와 다중 센서 데이터 수집 및 액추에이터 제어를 수행하는 하위 제어기인 ESP32-S3 기반의 이중 제어 구조를 구축하였다. 로봇의 기동 프레임은 하중 지지와 강성 확보에 유리하고 확장성과 가격이 상대적으로 좋은 3030 기반의 알루미늄 프로파일을 기반으로 제작하였으며 아크릴 판을 덧대어 회로기판과 전력계통을 설치할 수 있도록 설계하였다. 동력계는 ODrive 3.6 드라이버로 제어되는 36V 5.5인치 인휠 모터와 주행 안정성이 검증된 6인치 보조바퀴를 조합하여 최적의 주행 안정성을 확보하고 LIDAR C1 센서를 활용한 주변 환경의 SLAM 레이더 맵핑 및 NAVI2를 통한 자율주행 알고리즘을 설치하여 이를 활용해 4종 복합 수질 센서로부터 취합된 센서 데이터를 ROS2로 토픽을 통해 가공하고. 여기서 더 나아가 센서 프로브를 안전하게 운용하기 위한 엔드이펙터 구조를 설계하고 있으며, 초동 방역 목적의 UV-C 소독 모듈 외에도 오염 영역의 정화를 위한 소독약 투하 매커니즘, 산소 공급을 위한 공기 공급 장치 등 다각적인 방면에서 정화기법의 연동 및 추가 장착 등 상황에 맞는 모듈을 장착할 수 있도록 개발한다.

[개발 역량]

3D프린터 모델링, 하드웨어 제작 및 가공, 설계 및 제작, ROS2 Jazzy 활용능력, 라즈베리 파이 프로그래밍, C/C/파이썬, LIDAR 활용능력

[지원 동기]
리눅스, ROS2 등 처음부터 배워야 할 것이 많지만 프로젝트를 개발하고 완수하면서 많이 배우고 완성 시키겠습니다.