Multi-Robot Information Sharing for Complementing Limited Perception: A Case Study of Moving Ball Interception

Poor sensor data because of uncertainty and hardware limitations results in a robot misinterpreting the state of its surrounding environment, leading to bad decisions and even-tually failure to successfully perform its desired tasks. These limitations can be overcome if a teammate robot with a better view shares its visual information. Our work aims to investigate why current approaches fail to effectively use teammate sensor data, propose an alternative where a teammate helps to better capture the state of the environment, and demonstrate that the robot can make better decisions when a teammate shares its perceptual data. Raw teammate sensor data is not meaningful unless provided a relative, geometric transform to place this data within another robot’s own egocentric coordinates. There are few approaches that are able to discover this relative localization accurately in sparse environments while remainin