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