Abstract
The openness of the environment brings great challenges to the swarm robotic system to cover the task area quickly and effectively. In this paper, a coverage method based on gradient and grouping (GGC) is proposed. What is novel about our proposed solution is that it is suitable for extremely simple robots that lack computing or storage power. Through the change of the robot gradient, the swarm robot system with very simple functions can effectively self-organize to cover the unknown task area. By grouping the swarm robots, each group can cover the task area in parallel, which greatly improves the coverage speed. We verified our proposed method through experimental simulation and found that the gradient and grouping-based method in this paper was superior to other methods in terms of coverage, coverage completion time, and other aspects. Simultaneously, the robustness of the proposed method is analyzed and admirable experimental results are obtained. Because the applicable robot is very simple, the method in this paper can be applied to the submillimeter swarm robot system, which will lay the foundation for micro medicine.
Highlights
Swarm robots are composed of a large number of simple agents with autonomous capabilities, local communication, and perceived energy
This paper proposes a self-organization blanket coverage method based on gradient and grouping for large-scale swarm robots, which can cover the unknown complex area effectively and quickly
The idea of self-organizing area coverage method based on gradient is as follows: Firstly, all robots are in the Initial status, and the robots initialize their gradient by monitoring the adjacent neighbors within dm in distance
Summary
Swarm robots are composed of a large number of simple agents with autonomous capabilities, local communication, and perceived energy. An artificial bee colony algorithm and particle swarm optimization algorithm was used to solve the sensor configuration problem [36], and the heuristic algorithm was used for scheduling These methods are not suitable for complex environments and large-scale robots.Teruel et al [37] proposed a distributed self-deployment mechanism (Centroidal Voronoi Tessellations (CVT), which enables the swarm robots to self-organize and evenly cover the dynamic region, greatly improving the convergence of the system through feedforward actions. This paper proposes a self-organization blanket coverage method based on gradient and grouping for large-scale swarm robots, which can cover the unknown complex area effectively and quickly.
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
