Multi-Agent Visual Coordination using Optical Wireless Communication

Communication is a key element in applying multi-agent reinforcement learning to a wide range of real-world scenarios. We focus on optical wireless communication (OWC), which is a practical solution to be used in various real situations where radio communication is not available, such as underwater or in a lot of radio noise environment. OWC is a method of communicating only with other agents in visual range using light, unlike radio wave like communication which is mostly assumed in existing research on multi-agent reinforcement learning. Due to limited communication, when OWC is used, overall performance is generally degraded from the case with full communication. In this paper, we propose a reinforcement learning method that learns visual coordination behavior using OWC. Our proposed visually cooperative behavior enables agents equipped with limited field of view (FOV) cameras to efficiently comprehend and imagine their surrounding environment through cooperative communication. Experimental results in simulation demonstrated that, using the proposed visual coordination method, multi-agents using OWC with general FOV show comparable performance to those with radio wave like full communication. Additionally, it has been demonstrated that this method can improve performance in various multi-agent reinforcement learning algorithms. We also implement OWC devices on real mobile robots and demonstrated the proposed multi-agent operation.