Area Coverage Optimization Using Heterogeneous Robots: Algorithm and Implementation

作者：Miah Md Suruz^*; Knoll Jacob

来源：IEEE Transactions on Instrumentation and Measurement, 2018, 67(6): 1380-1388.

DOI：10.1109/TIM.2018.2800178

• Area coverage
• mobile robots
• optimization
• robot operating system (ROS)
• voronoi tessellation

This paper advances the previous theoretical work of authors by conducting experiments on a generalized coverage optimization algorithm using a team of heterogeneous mobile robots. A scalar measure (herein called the density) of the environment defines a nonuniform coverage metric of the area. Mobile robots are spatially configured such that their asymptotic placements in an area maximize the nonuniform coverage metric. Over the last fifteen years, a large body of research work has been conducted in solving the area coverage optimization problem where the focus was mainly on theoretical results followed by mostly numerical simulations. In some cases, the coverage optimization algorithms were validated with experimental results, but the implementation platforms were suitable to specific homogeneous robot platforms. Here, the emphasis is on the real-time implementation of the authors' previously published theoretical results on area coverage optimization problems using a team of heterogeneous mobile robots. The robots are heterogeneous in the sense that they have different actuator limits, physical dimensions, and processing capabilities. The modularity of the algorithm stems from the fact that the additional hardware/software architecture is open-source and can be applied to different robots regardless of their internal electromechanical system architectures. The algorithm is implemented using the emerging robot operating system in a multithreaded manner. A commercial robot simulator was used to validate the coverage performance followed by a set of experiments conducted in an indoor environment.

• 出版日期2018-6