A flexible scaling self-healing method for morphology of swarm robots

Abstract

The paper studies the formed body after completing its autonomous formation task and then proposes a self-healing method that flexibly scales with the scale of the loss in the situation that a large-scale swarm robot is locally missing due to external disturbances. With the stratified mechanism that includes layer-by-layer separation, layer-by-layer filling and iteration loop, the macro-level behavior of a swarm robot is transformed to the local action of an individual robot within the edge layers of the current aggregate. Based on the existing formation technique, driven by the shape genes of the formed body and the changes in the scale of population, the self-healing goal of the large scale of population is transformed into the similar scale of the formed body after scaling. Through the self-healing movement control method centered on individual behavior rules, the bottom-up self-healing configuration is presented on a scaled scale. The paper verifies the feasibility and scalability of this novel method through simulations. The maximum number of robots can reach tens of thousands. Finally, the self-healing method is used to implement the Cilibot robot, a hardware system developed by our laboratory.

Keywords

• swarm robot
• local missing
• constant density scaling
• self-healing
• verification