第1 章 智能體運(yùn)動(dòng)規(guī)劃研究概述·······································································（1）
1.1 研究背景···························································································（1）
1.2 研究現(xiàn)狀···························································································（1）
1.3 研究思路···························································································（8）
第2 章 運(yùn)動(dòng)規(guī)劃中的智能體多層次行為模型框架設(shè)計(jì)·········································.（11）
2.1 環(huán)境建模方法··················································································.（11）
2.1.1 三角剖分法···········································································.（11）
2.1.2 可視圖方法···········································································.（12）
2.1.3 Voronoi 圖法··········································································.（12）
2.1.4 隨機(jī)采樣法···········································································.（13）
2.2 運(yùn)動(dòng)規(guī)劃方法··················································································.（16）
2.2.1 全局運(yùn)動(dòng)規(guī)劃········································································.（16）
2.2.2 局部運(yùn)動(dòng)規(guī)劃········································································.（20）
2.3 智能體多層次行為模型設(shè)計(jì)································································.（23）
2.3.1 智能體介紹···········································································.（23）
2.3.2 現(xiàn)有智能體行為模型框架·························································.（24）
2.3.3 智能體多層次行為模型框架······················································.（27）
第3 章 基于多信息域、多分辨率場(chǎng)景描述模型的多層次運(yùn)動(dòng)規(guī)劃算法研究··············.（31）
3.1 相關(guān)工作························································································.（31）
3.2 層次化運(yùn)動(dòng)規(guī)劃算法總體思路·····························································.（34）
3.2.1 問(wèn)題描述··············································································.（34）
3.2.2 總體思路··············································································.（35）
3.3 全局層次上的多樣化引導(dǎo)路徑生成·······················································.（36）
3.3.1 高層時(shí)空約束的表示·······························································.（36）
3.3.2 全局概率路徑圖的生成····························································.（38）
3.3.3 全局多樣化引導(dǎo)路徑的生成······················································.（39）
3.4 局部層次上的多樣化運(yùn)動(dòng)路徑生成·······················································.（41）
3.4.1 局部高分辨率概率路徑圖的生成················································.（41）
3.4.2 局部多樣化運(yùn)動(dòng)路徑的生成······················································.（42）
3.5 動(dòng)態(tài)障礙情況下的運(yùn)動(dòng)路徑重新規(guī)劃問(wèn)題··············································.（43）
3.5.1 運(yùn)動(dòng)路徑的重新規(guī)劃·······························································.（43）
3.5.2 概率路徑圖的動(dòng)態(tài)更新····························································.（44）
3.6 仿真實(shí)驗(yàn)與結(jié)果分析·········································································.（45）
第4 章 多智能體避碰行為研究·······································································.（48）
4.1 相關(guān)工作························································································.（48）
4.2 避碰行為的基本概念與問(wèn)題描述··························································.（50）
4.2.1 基本概念··············································································.（50）
4.2.2 問(wèn)題描述··············································································.（51）
4.3 反應(yīng)式避碰行為模型·········································································.（52）
4.4 基于最小代價(jià)原則的預(yù)測(cè)式避碰行為模型··············································.（57）
4.4.1 最小代價(jià)原則········································································.（57）
4.4.2 基于最小代價(jià)原則的預(yù)測(cè)式避碰行為建�！ぁぁぁぁぁぁぁぁぁぁぁぁぁぁぁぁぁぁぁぁぁぁぁぁぁぁぁぁぁぁぁぁぁぁぁ�.（58）
4.5 仿真實(shí)驗(yàn)與結(jié)果分析·········································································.（63）
第5 章 基于增廣物理仿真的運(yùn)動(dòng)規(guī)劃多任務(wù)約束建模分析與優(yōu)化求解····················.（67）
5.1 相關(guān)工作························································································.（67）
5.2 問(wèn)題描述························································································.（70）
5.3 控制圍欄函數(shù)基礎(chǔ)背景知識(shí)································································.（70）
5.4 基于控制圍欄函數(shù)的多任務(wù)約束統(tǒng)一描述與運(yùn)動(dòng)路徑動(dòng)力學(xué)物理仿真優(yōu)化生成···.（71）
5.4.1 基于控制圍欄函數(shù)的多任務(wù)約束統(tǒng)一描述····································.（72）
5.4.2 增廣物理仿真框架下的智能體運(yùn)動(dòng)路徑優(yōu)化生成···························.（74）
5.5 仿真實(shí)驗(yàn)與結(jié)果分析·········································································.（77）
5.5.1 可生成多樣化行為的智能體運(yùn)動(dòng)路徑優(yōu)化計(jì)算······························.（77）
5.5.2 自動(dòng)駕駛中自適應(yīng)巡航運(yùn)動(dòng)路徑優(yōu)化計(jì)算····································.（81）
5.6 多智能體運(yùn)動(dòng)規(guī)劃仿真演示軟件設(shè)計(jì)開(kāi)發(fā)··············································.（83）
5.6.1 演示軟件設(shè)計(jì)開(kāi)發(fā)··································································.（83）
5.6.2 多智能體運(yùn)動(dòng)路徑生成測(cè)試······················································.（85）
第6 章 多任務(wù)約束時(shí)空融合處理機(jī)制研究························································.（87）
6.1 相關(guān)工作························································································.（87）
6.2 具有速度和加速度約束的多智能體時(shí)間最優(yōu)軌跡規(guī)劃·······························.（88）
6.2.1 問(wèn)題描述··············································································.（88）
6.2.2 算法思路及流程·····································································.（92）
6.2.3 可達(dá)集與可達(dá)速度區(qū)間的計(jì)算···················································.（95）
6.2.4 利用VIP 算法計(jì)算時(shí)間最優(yōu)軌跡················································.（97）
6.2.5 仿真實(shí)驗(yàn)與結(jié)果分析·······························································.（99）
6.3 基于控制圍欄函數(shù)描述的多任務(wù)約束時(shí)空融合處理··································（107）
6.3.1 同時(shí)段下多任務(wù)約束時(shí)序沖突的自動(dòng)優(yōu)化處理······························（107）
6.3.2 仿真實(shí)驗(yàn)與結(jié)果分析·······························································（111）
第7 章 滿(mǎn)足時(shí)空約束要求的多智能體運(yùn)動(dòng)規(guī)劃在城市維穩(wěn)處突行動(dòng)仿真場(chǎng)景下的應(yīng)用····.（115）
7.1 應(yīng)用場(chǎng)景描述··················································································（115）
7.2 可視化仿真·····················································································（117）
7.2.1 仿真參數(shù)設(shè)置········································································（117）
7.2.2 仿真結(jié)果演示········································································（118）
第8 章 深度強(qiáng)化學(xué)習(xí)在運(yùn)動(dòng)規(guī)劃中的應(yīng)用探索研究············································（124）
8.1 相關(guān)工作························································································（124）
8.2 深度強(qiáng)化學(xué)習(xí)算法探索效率提升策略研究··············································（126）
8.2.1 基本思路··············································································（127）
8.2.2 遺傳算法和DDPG 算法相結(jié)合的DRL 算法探索效率提升策略··········（129）
8.2.3 仿真實(shí)驗(yàn)與結(jié)果分析·······························································（132）
8.3 基于深度強(qiáng)化學(xué)習(xí)的多智能體避碰行為生成···········································（134）
8.3.1 問(wèn)題描述與基本思路·······························································（134）
8.3.2 仿真實(shí)驗(yàn)與結(jié)果分析·······························································（135）
8.4 下一步展望·····················································································（136）
參考文獻(xiàn)······································································································（137）