FUZHUAN: Day 9-10 — SCRUM and PM Report

FUZHUAN 2024-12-21 00:48:58
Which course does this assignment belong toEE301
Where are the requirements for this assignment?Teamwork—beta Spring
Team Name

FUZHUAN

The objective of this assignmentDay 9-10 — SCRUM and PM Report
Other Reference DocumentsMethod of Construction ( 《构建之法》)

目录

SCRUM Part

PM Report

Expected Tasks Overview

Completed Tasks

Remaining Tasks

Burndown Chart

Changes in Task Volume


SCRUM Part

Team MemberAccomplishmentsTime SpentRemaining TasksIssues/ProblemsPlan for Tomorrow
Zhang YuxinCompleted final testing, fixed any remaining issues.6 hoursFinalize documentation and handover.Minor bugs found in final user flow.Conduct last testing on product purchase flow and finalize handover.
Luo YuxinFinalized product pages, made last adjustments based on feedback.5 hoursConduct final cross-browser testing.UI inconsistencies between browsers.Conduct final testing and resolve UI inconsistencies.
Yang RuoxinConducted final testing on all user flows.5 hoursFinalize documentation and submit for review.Some test cases failed in edge conditions.Resolve edge case issues and prepare final project review.
Lin JiahuiFinalized payment system and integration.6 hoursPrepare handover and final documentation.Final adjustments in payment gateway security.Ensure final security checks for payment system.
Sun XingCompleted final load testing and optimization of APIs.5 hoursDocument API performance and optimization.Stress testing results showed minor API lag.Finalize documentation for API optimizations and finalize stress testing.
Chen YikeFinalized database performance tuning and completed documentation.5 hoursComplete final query optimization report.Query performance slightly below expectations on heavy data sets.Finalize database optimization documentation and reporting.

 


PM Report

Expected Tasks Overview

TaskEstimated TimeIssues Count
Final testing and bug fixes10 hours2
Documentation and project review6 hours1

Completed Tasks

TaskTime SpentIssues Completed
Final testing and bug fixes8 hours2
Documentation and project review6 hours1

Remaining Tasks

TaskRemaining TimeRemaining Issues
Final testing and bug fixes2 hours1
Documentation and project review0 hours0

Burndown Chart

 

Changes in Task Volume

No major changes were encountered during the final testing phase, as all tasks were largely as expected. However, some minor issues were found with the final user flow, which extended the bug-fixing tasks.

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内容概要:本文围绕水陆两栖无人机的任务规划与执行问题,提出了一种基于Matlab实现的智能路径规划解决方案,重点融合粒子群优化算法(PSO)与遗传算法(GA)进行三维环境下的避障路径规划。研究系统性地构建了从复杂地形建模、任务需求分析到算法设计与仿真实验的完整流程,实现了在多约束、动态障碍物等复杂环境下无人机的高效任务调度。通过对GA与PSO两种智能优化算法在路径长度、收敛速度、路径平滑度及稳定性等方面的对比分析,深入探讨了各自在无人机路径规划中的适用场景与性能差异,验证了所提方法在提升任务执行效率与安全性方面的有效性。该方案不仅适用于水陆交互通用场景,也为多模态无人系统自主导航提供了可扩展的技术框架。; 适合人群:具备一定Matlab编程能力和算法基础,从事无人机路径规划、智能优化算法研究、自动化控制或相关领域科研工作的研究生、科研人员及工程技术人员。; 使用场景及目标:①应用于水陆两栖无人机在复杂自然环境(如江河湖海与陆地交错区域)中的自主巡航与任务执行;②比较遗传算法与粒子群算法在三维动态路径规划中的优化性能,指导实际工程中算法选型;③为多约束条件下无人系统的自主决策与实时避障提供算法支持与仿真验证平台。; 阅读建议:建议读者结合提供的Matlab代码进行动手实践,重点关注两种算法的数学建模过程、适应度函数设计、参数调优策略及路径生成逻辑,通过仿真实验直观对比算法性能差异,深入理解智能优化算法在复杂路径规划问题中的应用机制与优化潜力。

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