ASAPs: Asynchronous Hybrid Self-Reconfiguration Algorithm for Porous Modular Robotic Structures

Abstract

Programmable matter refers to material that can be programmed to alter its physical properties, including its shape. Such matter can be built as a lattice of attached robotic modules, each seen as an autonomous agent with communication and motion capabilities. Self-reconfiguration consists in changing the initial arrangement of modules to form a desired goal shape, and is known to be a complex problem due to its algorithmic complexity and motion constraints. In this paper, we propose to use a max-flow algorithm as a centralized global planner to determine the concurrent paths to be traversed by modules through a porous structure composed of 3D Catoms meta-modules with the aim of increasing the parallelism of motions, and hence decreasing the self-reconfiguration time. We implement a traffic light system as a distributed asynchronous local planning algorithm to control the motions to avoid collisions. We evaluated our algorithm using VisibleSim simulator on different self-reconfiguration scenarios and compared the performance with an existing fully distributed synchronous self-reconfiguration algorithm for similar structures. The results show that the new method provides a significant gain in performance.

A novel distributed meta-module motion design for modular robotic systems based on grid partition method

“…26 Parada et al 27 gave a meta-module design to realize expand and contract motions with rigid modules and showed the criterion of minimum scale of the metamodule in tunneling algorithms for reconfiguration. The max-flow algorithm 28,29 is designed for porous meta-module motion under the purely geometric model. With the centralized global planner, the reconfiguration process can be realized efficiently.…”