In this paper, the collective motion of self-driven robots is studied experimentally and theoretically. In the channel, the flowrate of robots increases with the density linearly, even if the density of the robots tends to 1.0. There is no abrupt drop in the flowrate, similar to the collective motion of ants. We find that the robots will adjust their velocities by a serial of tiny collisions. The speed-adjustment will affect both robots involved in the collision, and will help to maintain a nearly uniform velocity for the robots. As a result, the flowrate drop will disappear. In the motion, the robots neither gather together nor scatter completely. Instead, they form some clusters to move together. These clusters are not stable during the moving process, but their sizes follow a power-law-alike distribution. We propose a theoretical model to simulate this collective motion process, which can reproduce these behaviors well. Analytic results about the flowrate behavior are also consistent with experiments.
This paper compares the experiment and simulation results of vehicular traffic merging flow and granular merging flow. The flow rate behavior and the phase diagram of the two systems are reported and compared. Although the two systems show different flow rate behavior and phase transition phenomenon, they can be optmized with similar methods.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.