109 lines
5.3 KiB
TOML
109 lines
5.3 KiB
TOML
# =============================================================================
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# UAVSearch 完整配置 — 修改此文件即可运行，无需 CLI 参数
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# =============================================================================
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# -----------------------------------------------------------------------------
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# [problem] 问题定义
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# -----------------------------------------------------------------------------
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[problem]
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width = 1000.0 # 空域宽度 (m)
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height = 800.0 # 空域高度 (m)
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uavs = 7 # UAV 数量
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radius = 50.0 # 传感器半径 (m)
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speed = 15.0 # 飞行速度 (m/s)
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depot_service = 60.0 # 站内换电/服务时间 (s)
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seed = 64 # 随机种子（基线部署与优化器）
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# 分区模式
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# workload — 栅格最近站点划分（推荐，优化平滑）
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# lloyd — Lloyd 松弛栅格划分
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# voronoi — 站点 Voronoi 图
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# uniform — 等面积条带（legacy，配 boustrophedon 常用）
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partition = "voronoi"
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# 路径规划器
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# mtsp — 栅格航点 + TSP 闭环（推荐）
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# boustrophedon — 牛耕/条带扫描
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planner = "mtsp"
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# 仿真指标栅格密度（见下方说明，不直接控制路径航点密度）
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# 仿真栅格边长 cell_size = radius / grid_density
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# 越大 → 栅格越细 → T_max/覆盖率/重叠率估计越准，但仿真更慢
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# 推荐：mtsp 用 4~6；boustrophedon 用 3~5（路径已是条带，无需过细）
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grid_density = 6.0
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# uniform 分区条带方向；也影响 boustrophedon 扫描轴（auto 时 vertical→水平扫描）
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# auto | vertical | horizontal
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strip_direction = "auto"
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# Lloyd 分区迭代次数（仅 partition = "lloyd" 时生效）
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lloyd_iterations = 6
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# 仿真时间步长 (s)
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sim_dt = 0.5
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# 站点搜索边界内缩比例（相对空域宽/高）
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bounds_margin = 0.05
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# -----------------------------------------------------------------------------
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# [planner.boustrophedon] 牛耕规划器（planner = "boustrophedon" 时生效）
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# -----------------------------------------------------------------------------
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# 条带间距 = sweep_width_ratio × radius
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# 默认 2.0 → 条带间距 = 2r，与传感器直径一致，保证无漏覆盖
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# 调小（如 1.6）→ 条带更密、路径更长、覆盖冗余更大
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# 调大（如 2.2）→ 条带更疏，可能出现漏覆盖
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[planner.boustrophedon]
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sweep_width_ratio = 2.0
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# 扫描轴：x = 水平扫描线（条带沿 Y 堆叠）；y = 垂直扫描线
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# auto — 由 strip_direction 推断（vertical→x，horizontal→y）
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sweep_axis = "auto"
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# -----------------------------------------------------------------------------
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# [planner.mtsp] mTSP 规划器（planner = "mtsp" 时生效）
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# -----------------------------------------------------------------------------
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# 航点间距 = waypoint_spacing_factor × radius
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# 默认 √2 ≈ 1.414 → 栅格对角线间距，相邻航点传感器圆相交无漏
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# 调小 → 航点更密、路径更长；调大 → 航点更疏，可能漏覆盖
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[planner.mtsp]
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waypoint_spacing_factor = 1.0
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# -----------------------------------------------------------------------------
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# [simulation] 仿真
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# -----------------------------------------------------------------------------
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[simulation]
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duration = 200.0 # 基线/最终报告仿真时长 (s)
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opt_duration = 100.0 # 优化搜索阶段每次评估的仿真时长 (s)
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fast_eval_max_duration = 100.0 # fast_eval 仿真时长上限 (s)
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fast_eval_grid_density_cap = 3.0 # fast_eval 时 grid_density 上限
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show_progress = true # 是否显示 tqdm 进度条
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# -----------------------------------------------------------------------------
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# [objective] 优化目标
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# -----------------------------------------------------------------------------
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# 复合目标 J = weight_t_max × T* + weight_coverage × (1-覆盖率) + weight_overlap × 重叠率
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# T* = T_max（primary = max_revisit）或 P_max（primary = max_patrol_period）
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[objective]
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primary = "max_revisit" # max_revisit | max_patrol_period
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weight_t_max = 1.0
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weight_coverage = 220.0
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weight_overlap = 100.0
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# -----------------------------------------------------------------------------
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# [optimizer] 优化器（当前使用 method 指定的那一组）
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# -----------------------------------------------------------------------------
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[optimizer]
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method = "mapso" # differential_evolution | local | hybrid | mapso
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maxiter = 5 # DE/MAPSO 最大代数；hybrid 时 DE 用 maxiter//2
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popsize = 8 # 种群规模
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verbose = true # 打印每次评估日志
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min_separation_ratio = 0.5 # 站点最小间距 = ratio × radius
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# MAPSO（method = "mapso" 时生效）
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[optimizer.mapso]
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w = 0.729
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c1 = 1.494
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c2 = 1.494
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vmax_ratio = 0.2
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# 差分进化（method = differential_evolution 或 hybrid 的第一阶段）
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[optimizer.differential_evolution]
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tol = 0.05
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atol = 0.05
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polish = false
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# 局部精修 L-BFGS-B（method = local 或 hybrid 的第二阶段）
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[optimizer.local]
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maxiter = 40
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# -----------------------------------------------------------------------------
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# [run] 运行
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# -----------------------------------------------------------------------------
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[run]
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optimize = true
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save = "output/dashboard.png"
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show = true |