Module Addition-Aware Dynamic Shape Recognition for Lattice-Based Modular Robots

Self-Reconfigurable Modular Robots typically consist of high number of modules with uniform docking interfaces, allowing them to transform into various shape. Recognizing the shape of such a system composed of hundreds of modules is a significant challenge. Given a new configuration, a modular robots system must be able to determine and update its shape dynamically and in a distributed manner. In a previous work, we developed an algorithm that identifies overlapping boxes to cover the entire robot configuration through message-passing, enabling robots to determine a representation of their current shape. However, this algorithm was static and did not react to changes in real time. In this paper, we introduce an updated shape recognition algorithm that dynamically and in real-time recognizes the addition of modules to update the shape description of the entire configuration using local information. The dynamic algorithm to update the shape description is tested in a simulated environment and compared to re-executing the shape recognition algorithm on the whole configuration. The results show the efficiency of our algorithm in updating the robot’s current shape in real time.