FUZHUAN:Day 1-2 — SCRUM and PM Report

FUZHUAN 2024-12-21 00:27:51
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 1-2 — SCRUM and PM Report
Other Reference DocumentsMethod of Construction ( 《构建之法》)

 


目录

Day 1-2 — SCRUM and PM Report

SCRUM Part

PM Report

Expected Tasks Overview

Completed Tasks

Remaining Tasks

Burndown Chart

Changes in Task Volume


Day 1-2 — SCRUM and PM Report

SCRUM Part

Team MemberAccomplishmentsTime SpentRemaining TasksIssues/ProblemsPlan for Tomorrow
Zhang YuxinCompleted core functionality testing, fixed major bugs.6 hoursFinish minor bug fixes and integrate with frontend.Backend and frontend integration issues.Review and integrate backend functionality with frontend, fix remaining bugs.
Luo YuxinCoordinated with backend to fix frontend bugs.5 hoursTest the integration of backend services.UI rendering issues with backend data.Conduct integration testing, collaborate with backend to ensure smooth functionality.
Yang RuoxinHelped with debugging frontend issues.4 hoursFinalize UI design and adjust user flow.UI consistency across pages.Continue working on UI consistency and design adjustments.
Lin JiahuiCompleted user login and registration features.6 hoursImplement user settings page.Authentication issues with user sessions.Focus on improving user login/logout functionality and settings page.
Sun XingDeveloped API endpoints for user management.5 hoursComplete remaining API endpoints.API response time too slow.Work on optimizing API responses and improving performance.
Chen YikeFixed database schema and integrated with API.5 hoursImplement query optimization.Database query bottleneck issues.Optimize database queries and ensure faster data retrieval.

PM Report

Expected Tasks Overview

TaskEstimated TimeIssues Count
Core functionality testing16 hours5
Frontend bug fixes10 hours3
Backend and frontend integration8 hours2

Completed Tasks

TaskTime SpentIssues Completed
Core functionality testing12 hours4
Frontend bug fixes8 hours2
Backend and frontend integration6 hours2

Remaining Tasks

TaskRemaining TimeRemaining Issues
Core functionality testing4 hours1
Frontend bug fixes2 hours1
Backend and frontend integration2 hours1

Burndown Chart

 

Changes in Task Volume

During the initial stages, we discovered that the backend integration was more complex than initially expected, requiring more time than anticipated. This added 2 hours to the initial plan. Additionally, some unforeseen issues related to the frontend user interface were discovered during testing, leading to an increase in the number of issues in the bug tracker.

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内容概要:本文系统研究了AGV(自动导引车)与AMR(自主移动机器人)在运动规划与导航领域的多种核心算法,涵盖Dijkstra、A*、Theta*、JPS、D* Lite、LPA*、RRT系列(RRT、RRT-Connect、启发式RRT)、蚁群算法、沃罗诺伊图路径规划及PID控制等典型方法,并基于Matlab平台实现了算法仿真与对比分析。研究聚焦于复杂工业环境下的机器人自主导航问题,深入探讨各类算法在路径最优性、计算效率、动态避障能力与环境适应性等方面的性能差异,旨在为智能物流、智能制造及自动化仓储等应用场景提供高效可靠的导航解决方案。同时,资源复现了IEEE顶刊研究成果,增强了学术参考价值。; 适合人群:具备一定Matlab编程基础与机器人学基础知识,从事机器人路径规划、智能控制、自动化系统开发等相关方向的科研人员、工程技术人员及高校研究生及以上层次的学习者。; 使用场景及目标:①应用于工厂、仓库等实际场景中AGV/AMR的路径规划与自主导航系统设计与优化;②作为科研项目、学位论文或算法竞赛的技术支撑,用于多算法性能对比、仿真验证与方案选型;③深入理解经典与现代路径规划算法的原理、实现机制及其在动态环境中的适应性演化。; 阅读建议:建议结合提供的Matlab代码进行动手实践,重点开展不同算法在同一仿真环境下的路径生成效果与运行效率对比实验,关注算法在动态障碍物规避和实时重规划方面的能力表现,同时可进一步拓展至多机器人协同导航、复杂地形适应等高级研究方向进行深化探索。

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