CraftEnv: A Flexible Collective Robotic Construction Environment for Multi-Agent Reinforcement Learning

CraftEnv is a flexible Collective Robotic Construction (CRC) environment for Multi-Agent Reinforcement Learning (MARL) research. CraftEnv can be used to study how artificial intelligent agents may learn to cooperate and solve complex real world tasks, such as collective construction and intelligent warehousing. The environment contains a set of collective construction tasks, which require a group of robotic vehicles to cooperate and learn to build different constructions efficiently. There are different elements in the CraftEnv, such as smartcars, blocks, and slopes. The smartcars can use the blocks and slopes to build different structures. The CraftEnv is highly flexible and simple to use, which enables creative and quick task-designs. The environment is written in python and can be rendered using PyBullet. The simulation is built based on real world robotic systems, designed with real-world constraints in mind. The learned policy can be transferred to the real world robotic system. CraftEnv is tailored for effective use by the research community and pushing forward collective intelligence and swarm technology.