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libMultiRobotPlanning

Library with search algorithms for task and path planning for multi robot/agent systems

AI EngineeringPrompt & ScaffoldC++
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创建于 2017-11-06 · 更新于 2026-10-11 · 今日第 11928 名
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whoenigct2034kylevedder

whoenig/libMultiRobotPlanning 排名第 11,928，有 1,042 个星标。

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whoenig/libMultiRobotPlanning 排名第 11,928，此处有 8 个同类条目；kunal12203/GrapeRoot 排名第 11,931。

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关键参数与规格
关键参数与规格
参数值
语言C++
类别AI Engineering
子类别Prompt & Scaffold
关键词Planning, Search
星标数1,042
分叉数239
贡献者4
创建日期2017-11-06
更新日期2026-10-11
1 天星标数0
7 天星标数1
排名11,928
上次排名11,841
排名变化-87
7 天星标排名10,267
上次 7 天星标排名8,357
7 天星标排名变化-1,910
总星标排名10,824
上次总星标排名10,799
总星标排名变化-25
国家Germany
README 摘录

libMultiRobotPlanning libMultiRobotPlanning is a library with search algorithms primarily for task and path planning for multi robot/agent systems. It is written in C++(14), highly templated for good performance, and comes with useful examples. The following algorithms are currently supported: Single-Robot Algorithms A* A* epsilon (also known as focal search) SIPP (Safe Interval Path Planning) Multi-Robot Algorithms Conflict-Based Search (CBS) Enhanced Conflict-Based Search (ECBS) Conflict-Based Search with Optimal Task Assignment (CBS-TA) Enhanced Conflict

-Based Search with Optimal Task Assignment (ECBS-TA) Prioritized Planning using SIPP (example code for SIPP) Assignment Algorithms Minimum sum-of-cost (flow-based; integer costs; any number of agents/tasks) Best Next Assignment (series of optimal solutions) Building Tested on Ubuntu 16. Targets : Build examples, only : build doxygen documentation : Re-format all source files : Run linter & static code analyzer : Run unit-tests Run specific tests Run example instances ECBS python3 . /cbs_roadmap -i mapf_simple1_roadmap_annotated.

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记录了多少星标和分叉？

whoenig/libMultiRobotPlanning 有 1,042 个星标和 239 个分叉。

仓库排名是多少？

whoenig/libMultiRobotPlanning 排名第 11,928。

记录的语言和类别是什么？

whoenig/libMultiRobotPlanning 有 1,042 个星标，语言为 C++，类别为 AI Engineering。

哪个仓库排名最接近？

whoenig/libMultiRobotPlanning 与 kunal12203/GrapeRoot 比较，后者排名第 11,931，有 1,041 个星标。

README

libMultiRobotPlanning

libMultiRobotPlanning is a library with search algorithms primarily for task and path planning for multi robot/agent systems. It is written in C++(14), highly templated for good performance, and comes with useful examples.

The following algorithms are currently supported:

  • Single-Robot Algorithms

    • A*
    • A* epsilon (also known as focal search)
    • SIPP (Safe Interval Path Planning)

  • Multi-Robot Algorithms

    • Conflict-Based Search (CBS)
    • Enhanced Conflict-Based Search (ECBS)
    • Conflict-Based Search with Optimal Task Assignment (CBS-TA)
    • Enhanced Conflict-Based Search with Optimal Task Assignment (ECBS-TA)
    • Prioritized Planning using SIPP (example code for SIPP)

  • Assignment Algorithms

    • Minimum sum-of-cost (flow-based; integer costs; any number of agents/tasks)
    • Best Next Assignment (series of optimal solutions)

Building

Tested on Ubuntu 16.04.

mkdir build
cd build
cmake ..
make

Targets

  • make: Build examples, only
  • make docs: build doxygen documentation
  • make clang-format: Re-format all source files
  • make clang-tidy: Run linter & static code analyzer
  • make run-test: Run unit-tests

Run specific tests

python3 ../test/test_next_best_assignment.py TestNextBestAssignment.test_1by2

Run example instances

ECBS

./ecbs -i ../benchmark/32x32_obst204/map_32by32_obst204_agents10_ex1.yaml -o output.yaml -w 1.3
python3 ../example/visualize.py ../benchmark/32x32_obst204/map_32by32_obst204_agents10_ex1.yaml output.yaml

Generalized Roadmaps

CBS works on generalized graphs, with a particular focus on optional wait actions (e.g., this can be used with motion primitives as well). However, the roadmap annotation and visualization step currently assume a 2D Euclidean embedding and straight-line edges.

python3 ../tools/annotate_roadmap.py ../test/mapf_simple1_roadmap_to_annotate.yaml mapf_simple1_roadmap_annotated.yaml
./cbs_roadmap -i mapf_simple1_roadmap_annotated.yaml -o output.yaml
python3 ../example/visualize_roadmap.py mapf_simple1_roadmap_annotated.yaml output.yaml
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