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8 changes: 8 additions & 0 deletions build_latex_tactile.bat
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@echo off



rem 编译触觉本科毕业论文
pushd "%cd%\sim\tactile\undergraduate\"
xelatex -synctex=1 -interaction=nonstopmode hutbthesis_main.tex
popd
125 changes: 125 additions & 0 deletions tactile/content/chapter1.tex

Large diffs are not rendered by default.

246 changes: 246 additions & 0 deletions tactile/undergraduat/.gitignore
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## Core latex/pdflatex auxiliary files:
*.aux
*.lof
*.log
*.lot
*.fls
*.out
*.toc
*.fmt
*.fot
*.cb
*.cb2
.*.lb
clean.bat
elegant*-cn.pdf
elegant*-en.pdf
*.dates

## Intermediate documents:
*.dvi
*.xdv
*-converted-to.*
# these rules might exclude image files for figures etc.
# *.ps
# *.eps
# *.pdf

## Generated if empty string is given at "Please type another file name for output:"
.pdf

## Bibliography auxiliary files (bibtex/biblatex/biber):
*.bbl
*.bcf
*.blg
*-blx.aux
*-blx.bib
*.run.xml

## Build tool auxiliary files:
*.fdb_latexmk
*.synctex
*.synctex(busy)
*.synctex.gz
*.synctex.gz(busy)
*.pdfsync

## Auxiliary and intermediate files from other packages:
# algorithms
*.alg
*.loa

# achemso
acs-*.bib

# amsthm
*.thm

# beamer
*.nav
*.pre
*.snm
*.vrb

# changes
*.soc

# cprotect
*.cpt

# elsarticle (documentclass of Elsevier journals)
*.spl

# endnotes
*.ent

# fixme
*.lox

# feynmf/feynmp
*.mf
*.mp
*.t[1-9]
*.t[1-9][0-9]
*.tfm

#(r)(e)ledmac/(r)(e)ledpar
*.end
*.?end
*.[1-9]
*.[1-9][0-9]
*.[1-9][0-9][0-9]
*.[1-9]R
*.[1-9][0-9]R
*.[1-9][0-9][0-9]R
*.eledsec[1-9]
*.eledsec[1-9]R
*.eledsec[1-9][0-9]
*.eledsec[1-9][0-9]R
*.eledsec[1-9][0-9][0-9]
*.eledsec[1-9][0-9][0-9]R

# glossaries
*.acn
*.acr
*.glg
*.glo
*.gls
*.glsdefs

# gnuplottex
*-gnuplottex-*

# gregoriotex
*.gaux
*.gtex

# htlatex
*.4ct
*.4tc
*.idv
*.lg
*.trc
*.xref

# hyperref
*.brf

# knitr
*-concordance.tex
# TODO Comment the next line if you want to keep your tikz graphics files
*.tikz
*-tikzDictionary

# listings
*.lol

# makeidx
*.idx
*.ilg
*.ind
*.ist

# minitoc
*.maf
*.mlf
*.mlt
*.mtc[0-9]*
*.slf[0-9]*
*.slt[0-9]*
*.stc[0-9]*

# minted
_minted*
*.pyg

# morewrites
*.mw

# nomencl
*.nlg
*.nlo
*.nls

# pax
*.pax

# pdfpcnotes
*.pdfpc

# sagetex
*.sagetex.sage
*.sagetex.py
*.sagetex.scmd

# scrwfile
*.wrt

# sympy
*.sout
*.sympy
sympy-plots-for-*.tex/

# pdfcomment
*.upa
*.upb

# pythontex
*.pytxcode
pythontex-files-*/

# thmtools
*.loe

# TikZ & PGF
*.dpth
*.md5
*.auxlock

# todonotes
*.tdo

# easy-todo
*.lod

# xmpincl
*.xmpi

# xindy
*.xdy

# xypic precompiled matrices
*.xyc

# endfloat
*.ttt
*.fff

# Latexian
TSWLatexianTemp*

## Editors:
# WinEdt
*.bak
*.sav

# Texpad
.texpadtmp

# Kile
*.backup

# KBibTeX
*~[0-9]*

# auto folder when using emacs and auctex
./auto/*
*.el

# expex forward references with \gathertags
*-tags.tex

# standalone packages
*.sta

# generated if using elsarticle.cls
*.spl
38 changes: 38 additions & 0 deletions tactile/undergraduat/README.md
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# 本科毕业设计模板

湖南工商大学本科毕业设计模板。

# 使用
推荐使用 [texstudio](https://pan.baidu.com/s/1Is2-VR1z-tMYvmdinsVY_g?pwd=hutb) 或 [overleaf](https://cn.overleaf.com/) 进行论文撰写。

注:在 latex 2023 中编译成功,latex 2016 编译失败(需要更高的版本,其他版本的 latex 没试过)。

# 贡献
有任何对模板格式进行调整的可以提交 [Issues](https://github.com/OpenHUTB/undergraduate/issues) 或 [Pull Request](https://github.com/OpenHUTB/undergraduate/pulls) 。

# 选题
[选题列表](https://github.com/OpenHUTB/undergraduate/wiki/%E6%AF%95%E8%AE%BE%E9%80%89%E9%A2%98)


## 要求
1. 格式化、注释、文档翻译
2. 运行
3. 测试(例子通过)


## 初始化

1. 新建github工程

2. 运行`init_proj('PROJECT_NAME');`

3. 分配开发者


## 使用
克隆仓库
```shell
git clone --recursive https://github.com/OpenHUTB/undergraduate.git
```

# 贡献者
2 changes: 2 additions & 0 deletions tactile/undergraduat/cmdel.bat
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del /a /f *.xml *.bcf *.out *.log *.sav *.gz *.aux *.bbl *.bak *.dvi *.blg

7 changes: 7 additions & 0 deletions tactile/undergraduat/content/abstracten.tex
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%!TEX root = ../csuthesis_main.tex
\keywordsen{Pedestrian navigation, Reinforcement learning, Virtual simulation, Carla platform, Path planning, Obstacle avoidance}
\begin{abstracten}

With the advancement of smart city infrastructure, pedestrian navigation systems face increasing challenges in handling complex and dynamic urban environments. Traditional rule-based planning approaches struggle to adapt to real-time variations in pedestrian behavior. This study proposes a pedestrian navigation and control system based on the Unreal Engine and Carla platform, integrating reinforcement learning to optimize path planning and obstacle avoidance. By simulating realistic traffic scenarios, the system provides a high-fidelity virtual environment for training and evaluating intelligent agents. Reinforcement learning algorithms such as DQN and PPO are applied to improve navigation decision-making, guided by a multi-dimensional reward function that balances goal achievement, safety, and path efficiency. Experiments conducted in various simulation scenarios demonstrate the system's effectiveness in enhancing navigation accuracy, obstacle avoidance success, and overall planning efficiency. The results validate the feasibility of combining virtual simulation with reinforcement learning, offering a scalable and cost-effective approach to intelligent pedestrian navigation, and laying the groundwork for future research in multi-agent collaboration and intelligent traffic systems.

\end{abstracten}
9 changes: 9 additions & 0 deletions tactile/undergraduat/content/abstractzh.tex
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%!TEX root = ../csuthesis_main.tex
% 设置中文摘要
\keywordscn{行人导航\quad 强化学习\quad 虚拟仿真\quad Carla平台\quad 路径规划\quad 避障}
%\categorycn{TP391}
\begin{abstractzh}

智慧城市环境下交通环境对行人导航的要求更高,传统的基于规划路径的方式已经无法满足动态、复杂环境下行人的变化。为了提升行人导航的自适应能力和路径规划效率,本文在虚幻引擎与Carla中模拟一个真实的步行环境,构建一个具备强学习能力的行人控制和行人导航系统,动态仿真真实城市的交通环境,为行人强化学习模型提供测试、训练环境。本文将DQN、PPO等强化学习算法引入行人控制和行人避障,设计多维度奖励函数提升智能体对目标、避障、路径的理解能力,从而提升复杂交通环境下行人的决策能力。对行人导航、避障和路径多场景仿真评估,验证了系统在动态、复杂环境下的鲁棒性。验证了虚拟仿真和强化学习的融合可以拓展智慧交通应用领域,对多智能体协同智能交通未来发展提供可行性方案与路径支撑。

\end{abstractzh}
20 changes: 20 additions & 0 deletions tactile/undergraduat/content/acknowledgements.tex
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%!TEX root = ../csuthesis_main.tex
\begin{acknowledgements}

当我敲下论文的最后一个句号,本科生活也即将画上圆满的句点。回顾撰写论文的日子,虽困难重重,但我切实体会到了学术研究的严谨和价值,也对未来的研究生学术生活满怀期待。在此,我真心感谢所有给予我支持和帮助的老师、朋友和家人。

感谢虚幻引擎官方认证讲师谌嘉诚老师。我最初接触 UE4,是因为看到他开发的游戏。那些精彩作品在我心中种下了成为游戏开发者的种子,也促使我选定了现在这篇论文。谌老师的作品不仅引领我进入游戏开发领域,还激励我在这条路上不断探索。

感谢湖南工商大学前沿交叉学院、人工智能与先进计算学院、工商管理学院的全体老师,本科四年,是他们的辛勤教导为我奠定了扎实的专业基础。感谢我的导师王海东老师,没有您的帮助我无法完成论文。

感谢前沿交叉学院的刘利枚老师。不管是备考研究生时给我的鼓励,还是落榜时送来的安慰,都让我感受到温暖与力量,帮我在挫折中重新振作。感谢辅导员刘振坤老师,他为我的考研提供了许多实用指导,让迷茫的我找到了方向。还要感谢论文开题和中期答辩时提出宝贵意见的评审专家,他们的批评和建议让我的研究逻辑更严密,也为我未来的学术研究定下严谨基调。

感谢室友李勇、朱栋、全松林、资龙、邓哲,还有谭子钰、张子阳、杨钊等等我的大学好友们,以及我的女朋友李玲俊。四年同窗,我们一起学习、生活,分享成长中的喜怒哀乐。那些一起奋斗的日子和欢声笑语,都是我大学生活中最珍贵的回忆,也会成为我人生中最重要的一笔财富。

感谢我的父母和家人。他们一直包容理解我,支持我的每一个选择。在我焦虑迷茫时,给予精神鼓励和安慰,让我能专心备考考研、撰写论文。感谢妈妈在我人生关键节点为我指明方向,感谢爸爸尊重我的想法和选择,让我能按自己的意愿追逐梦想,感谢舅舅在求学路上给我的诸多帮助,让我感受到家人的温暖与力量。

最后,我也要感谢自己。大学四年,从初入校园的懵懂,到如今目标明确、步伐坚定,即使前路满是艰辛与挑战。希望未来,我能带着这份坚持和勇气,朝着目标不断奋进,在学术和人生道路上取得更好成绩 。

行文终有尽时,感激永不停止,谨以此论文献给所有关心帮助过我的人!

\end{acknowledgements}
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