整合软硬件的自动驾驶配送机器人，实现可靠运行。
A Unified AI, Embedded, Simulation, and Mechanical Design Approach to an Autonomous Delivery Robot
- 用树莓派5+ROS2做智能感知，ESP32实时控电机
- 实现确定性PID控制，电机故障可自动停机
- 适合想落地的机器人研发团队参考
本文提出一种集成机械工程、嵌入式系统与人工智能的全自主配送机器人。平台采用异构计算架构：树莓派5与ROS2负责基于AI的感知与路径规划，ESP32运行FreeRTOS实现电机的实时控制。通过精准选型与材料工程优化了机械结构，提升载重与机动性。重点解决资源受限环境下高计算负载的AI算法优化，以及ROS2主机与嵌入式控制器间的低延迟、高可靠性通信问题。实验表明，通过严格的内存与任务管理，实现了确定性的PID电机控制；借助AWS IoT监控与固件级电机断电保护，显著提升了系统可靠性。本研究展示了一种统一的多学科设计方法，构建出可实际部署的鲁棒自主配送系统。
原文摘要 · Abstract (English)
This paper presents the development of a fully autonomous delivery robot integrating mechanical engineering, embedded systems, and artificial intelligence. The platform employs a heterogeneous computing architecture, with RPi 5 and ROS 2 handling AI-based perception and path planning, while ESP32 running FreeRTOS ensures real-time motor control. The mechanical design was optimized for payload capacity and mobility through precise motor selection and material engineering. Key technical challenges addressed include optimizing computationally intensive AI algorithms on a resource-constrained platform and implementing a low-latency, reliable communication link between the ROS 2 host and embedded controller. Results demonstrate deterministic, PID-based motor control through rigorous memory and task management, and enhanced system reliability via AWS IoT monitoring and a firmware-level motor shutdown failsafe. This work highlights a unified, multi-disciplinary methodology, resulting in a robust and operational autonomous delivery system capable of real-world deployment.
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