Cooperative Localization of Multi-Robots Under Remote Interaction
Chang Liu, Jin Zhao, Nianyi Sun · 2023
In collaborative missions, each robot needs to have a clear understanding of the status among others, so there are many related works, such as virtual reality interaction or swarm jobs in real life. However, these types of collaboration still have some limitations: (i) Limited distance. Like virtual reality, users interact with others over the network in a pre-defined area and cannot move over more considerable distances; (ii) Weak/non-GPS signals. Like swarm jobs, relying only on localization information such as GPS tends to drift or interrupt, and significant location devices are hardly deployed on consumer-grade products. Given the above, we present a multi-robots collaborative localization framework based on Camera, IMU (Minimum unit for state estimation) and remote interaction module, which achieves not only globally consistent localization but also gets rid of the distance limitation of WIFI or Bluetooth. Meanwhile, we consider the scale ambiguity in visual-inertial collaborative localization. Finally, simulations and physical experiments validate the proposed multi-robots collaboration with remote interaction. Unlike traditional applications that rely on external devices (Motion Capture Devices or GPS), our system achieves globally consistent internal.