IEEE Maritime25: Distributed Multi-Vessel Autonomous Control System

The Maritime25 project pioneers a distributed, multi-vessel autonomous control system designed for intelligent patrolling, environmental monitoring, and rapid emergency response in complex water environments. Leveraging Python and ArduPilot, the system integrates IoT, autonomous navigation, and distributed control technologies to enable real-time task assignment, formation coordination, and remote supervision of multiple unmanned surface vessels (USVs). A lightweight MQTT-based message bus and custom JSON+MAVLink protocol ensure robust command dispatch, telemetry streaming, and "follow-the-leader" cluster coordination, supporting reliable and flexible deployment in dynamic scenarios.

In real-world applications, Maritime25 has been deployed for water quality sampling, target tracking, and emergency drills across lakes and rivers, demonstrating the transformative potential of USV swarms in smart water management. The system seamlessly switches between SITL simulation and Raspberry Pi + Pixhawk hardware, featuring fault-tolerant reconnection, mission recovery, and configurable QoS to adapt to unstable networks. Integrated backend (DroneKit) and frontend (MAVProxy/Mission Planner) streamline operations and mission execution.

For a detailed project story and application showcase, see the StoryMap report.

• Distributed Control: Custom MQTT+JSON protocol for synchronized multi-vessel missions and cluster coordination.
• Scenario Adaptability: Supports autonomous patrolling and task execution in lakes, rivers, and diverse water bodies.
• Fault Tolerance: Reconnection and state recovery mechanisms ensure stable operation in challenging environments.
• Integrated Solution: Unified backend logic (DroneKit) and ground station (MAVProxy) for seamless operation.
• Autonomous Features: Implements "follow-the-leader" formation and automated mission management for USV clusters.

MindRoll: Distributed Multiplayer Dice Game

Led core logic and system integration in a turn-based dice game using Python and Pygame. Designed and implemented a custom RPC protocol for real-time communication between players, ensuring robust turn synchronization and fault-tolerant reconnection. The project features a modular architecture, supports dynamic player joining, and provides a smooth multiplayer experience even under unstable network conditions. Responsible for both backend logic and user interface, focusing on user experience and system reliability.

CPU Design Using Vivado (Digital System Course Design)

Constructed a 32-bit CPU from scratch, including instruction set design, internal register management, and ALU implementation. Programmed and simulated the CPU in Verilog, then deployed it on a Xilinx FPGA board for real hardware testing. The project involved pipeline design, memory management, and debugging with Vivado tools. Emphasized modularity and scalability, allowing for future extension of instruction sets and peripherals. Demonstrated proficiency in digital logic, hardware description languages, and FPGA development workflow.

Research on the Sweeping Robot based on Optical Positioning Technology (Chinese National Training Program of Innovation)

Created new optical positioning modules and custom PCBs to enable precise indoor navigation for autonomous robots. Developed algorithms for real-time position estimation using analog signal processing and angle-of-arrival (AOA) techniques. Integrated Matlab-based simulation and Arduino-based hardware control, achieving centimeter-level accuracy in complex environments. The project is open-source and aims to provide a low-cost, scalable solution for robotics research and education. Responsible for system architecture, PCB layout, and experimental validation.

Multi-Directional Planar Robot with Edge AI Voice Control (National IoT Contest)

Designed and built a multi-directional mobile robot featuring intelligent voice control powered by edge AI. Utilized Espressif ESP32 Kit and integrated with Rainmaker Cloud for remote monitoring and control. Developed custom firmware for real-time voice recognition and command execution, enabling hands-free operation. The robot won both provincial and national awards for its innovative combination of IoT, AI, and robotics, and demonstrated practical applications in smart home and industrial automation scenarios.

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