JZT Shuttle Path Planning
2023
Summary
A warehouse automation path-planning prototype using A*, multi-vehicle conflict handling, and PyQt visualization.
Business Value
Provided core algorithm verification and simulation tools for AS/RS scheduling.
Engineering Depth
Demonstrates engineering implementation of complex operations research algorithms and GUI dev.
Evidence
Repository · Confidence Medium · Verified 2026-02-15
- Evidence level: strict review (core sections only show verifiable metrics)
- Source type: Repository / code records
- Source link: no public link provided, review against delivery records
- Verified at: 2026-02-15 (122 days ago, fresh evidence)
Rationale: Medium confidence: missing a public source link.
Background
仓储自动化需要智能调度算法。
Challenge
多车协同场景下容易出现节点占用冲突、路径交叉与潜在死锁，单车寻路算法难以直接复用。
Action and Results
Solution
- 实现路径搜索：基于 A* 完成仓储地图下的启发式路径求解。
- 处理多车冲突：引入冲突检测与优先级等待策略，解决多车协同时序冲突问题。
- 构建仿真工具：基于 PyQt5 开发地图编辑与路径可视化界面，支持调试与演示。
Result
完成多车路径规划原型验证，支持在仿真环境中直观展示路径搜索与冲突消解过程。
Key Signals
设计 A* 路径搜索算法，完成复杂仓储地图下的最优路径求解与启发式搜索实现。
实现多车冲突检测与优先级等待策略，处理节点占用与时序冲突，验证多车协同调度可行性。
开发 PyQt5 可视化仿真界面，支持地图编辑、起终点设置、路径步进调试及地图保存/加载。
Tech Stack
PythonA*CBSPyQt5ThreadPoolExecutorConcurrent