Kei18 / lacam3

Engineering LaCAM*: Towards Real-Time, Large-Scale, and Near-Optimal Multi-Agent Pathfinding (AAMAS-24)

lacam3

This is a code repository of the paper "Engineering LaCAM*: Towards Real-Time, Large-Scale, and Near-Optimal Multi-Agent Pathfinding" (AAMAS-24).

LaCAM(*) is a search-based algorithm for MAPF that can address large instances, e.g., with more than 1k agents. If you are interested in academic background, check out this talk and slides. There is a toy Python implementation as well.

This is the third generation of LaCAM: [lacam; AAAI-23] [lacam2; IJCAI-23]. The evolution is depicted below. My prior studies such as [pibt2; AIJ-22] and [mapf-IR; IROS-21] (concurrent with LNS) also play important roles.

Demo

lacam2 (left) vs. lacam3 (right, this repo) 🚀🪄

random-32-32-20.map, 409 agents, 30sec timeout, on Mac Book Pro (M2 Max)

Building

All you need is CMake (≥v3.16). The code is written in C++(17).

First, clone this repo with submodules.

git clone --recursive https://github.com/Kei18/lacam3.git && cd lacam3

Then, build the project.

cmake -B build && make -C build

Usage

build/main -i assets/random-32-32-10-random-1.scen -m assets/random-32-32-10.map -N 300 -v 3

The result will be saved in build/result.txt.

You can find details of all parameters with:

build/main --help

In fact, there are many hyperparameters (though I dislike). The default setting is usually an okay level to my knowledge.

Visualizer

This repository is compatible with kei18@mapf-visualizer.

Experiments

The experimental script is written in Julia ≥1.7. Setup may require around 10 minutes.

sh scripts/setup.sh

Edit the config file as you like. Examples are in scripts/config . The evaluation starts by following commands.

julia --project=scripts/ --threads=auto
> include("scripts/eval.jl"); main("scripts/config/mapf-bench.yaml")

The results will be saved in ../data/.

examples used in the paper

space utilization optimization

include("scripts/eval.jl"); target="scripts/config/exp_scatter"; foreach(x -> main("$(target)/common.yaml", x), filter(x -> !contains(x, "common"), glob("$(target)/*.yaml")))

Monte-Carlo configuration generator

include("scripts/eval.jl"); target="scripts/config/exp_mccg"; foreach(x -> main("$(target)/common.yaml", x), filter(x -> !contains(x, "common"), glob("$(target)/*.yaml")))

Licence

This software is released under the MIT License, see LICENSE.txt.

If possible, please consider contacting the author for commercial use. This is not a restriction, I just want to know about the use as an academic researcher.

Notes

install pre-commit for formatting

pre-commit install

simple test

ctest --test-dir ./build

others

• The grid maps and scenarios files are (mostly) from MAPF benchmarks, with some original ones. They are placed in ./scripts/map and ./scripts/scen.
• lacam4? I do not have such a plan currently...