mirror of
https://github.com/deepmodeling/Uni-Lab-OS
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9ef24b7768
Replace scipy differential_evolution with custom DE loop for per-device crossover, circular θ wrapping, and configurable mutation strategy (currenttobest1bin default, best1bin as turbo mode). Key improvements: - Graduate ALL hard constraints during DE (proportional penalty instead of flat inf), giving DE smooth gradient for reachability, min_spacing, etc. Binary inf preserved for final pass/fail reporting. - 2-axis sweep-and-prune AABB broad phase for collision pair pruning - Multi-seed injection from multiple seeder presets + Gaussian variants - snap_theta_safe: collision-check after angle snapping, revert on violation - Weight normalization (100 distance / 60 angle / 5× hard multiplier) - Constraint priority field (critical/high/normal/low → weight multiplier) with LLM intent interpreter setting priority per constraint type - Final success field now checks user hard constraints in binary mode - arm_slider added to mock checker reach table (1.07m) Tests: 202 passed, 24 new tests added (optimizer 7, constraints 6, broad_phase 11) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
67 lines
2.3 KiB
Python
67 lines
2.3 KiB
Python
"""2 轴 sweep-and-prune 宽相碰撞检测。
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对每个设备计算旋转后的 AABB，先沿 x 轴排序并剪枝，
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再用 y 轴交叠过滤。返回候选碰撞对（索引对列表），
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供后续 OBB SAT 精确检测使用。
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"""
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from __future__ import annotations
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from .models import Device, Placement
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def sweep_and_prune_pairs(
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devices: list[Device],
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placements: list[Placement],
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) -> list[tuple[int, int]]:
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"""2 轴 sweep-and-prune，返回 AABB 交叠的索引对。
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Args:
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devices: 设备列表，与 placements 一一对应。
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placements: 布局位姿列表。
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Returns:
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候选碰撞对列表，每个元素为 (i, j)，
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i < j，索引对应 placements 原始顺序。
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"""
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n = len(devices)
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if n < 2:
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return []
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# --- 计算每个设备旋转后的 AABB ---
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aabbs: list[tuple[float, float, float, float]] = []
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for dev, pl in zip(devices, placements):
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hw, hd = pl.rotated_bbox(dev)
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aabbs.append((pl.x - hw, pl.x + hw, pl.y - hd, pl.y + hd))
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# --- 按 xmin 排序，保留原始索引映射 ---
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sorted_indices = sorted(range(n), key=lambda k: aabbs[k][0])
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# --- 扫描 x 轴，y 轴过滤 ---
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candidates: list[tuple[int, int]] = []
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for si in range(len(sorted_indices)):
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i = sorted_indices[si]
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x_min_i, x_max_i, y_min_i, y_max_i = aabbs[i]
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for sj in range(si + 1, len(sorted_indices)):
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j = sorted_indices[sj]
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x_min_j, _x_max_j, y_min_j, y_max_j = aabbs[j]
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# 由于按 xmin 排序，x_min_j >= x_min_i
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if x_min_j > x_max_i:
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break # 后续设备 xmin 更大，不可能与 i 在 x 轴交叠
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# x 轴交叠确认，检查 y 轴
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if y_min_i <= y_max_j and y_min_j <= y_max_i:
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# 保证输出 (min_idx, max_idx) 方便去重和测试
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pair = (min(i, j), max(i, j))
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candidates.append(pair)
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return candidates
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def broad_phase_device_pairs(
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devices: list[Device],
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placements: list[Placement],
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) -> list[tuple[str, str]]:
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"""返回候选碰撞对的 device_id 字符串元组列表。"""
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index_pairs = sweep_and_prune_pairs(devices, placements)
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return [(placements[i].device_id, placements[j].device_id) for i, j in index_pairs]
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