Loading...
Please wait, while we are loading the content...
Similar Documents
Complete coverage problem of multiple robots with different velocities
| Content Provider | SAGE Publishing |
|---|---|
| Author | Li, Lin Shi, Dianxi Jin, Songchang Kang, Ying Xue, Chao Zhou, Xing Liu, Hengzhu Yu, XiaoXiao |
| Copyright Year | 2022 |
| Abstract | Complete coverage, which is integral to many robotic applications, aims to cover an area as quickly as possible. In such tasks, employing multiple robots can reduce the overall coverage time by appropriate task allocation. Several multi-robot coverage approaches divide the environment into balanced subareas and minimize the maximum subarea of all robots. However, balanced coverage in many situations, such as in the cases of robots with different velocities and heterogeneous multi-robot systems, may have inefficient results. This study addresses the unbalanced complete coverage problem of multiple robots with different velocities for a known environment. First, we propose a novel credit model to transform the unbalanced coverage problem into a set of single-objective optimization problems, which can find a combinational optimal solution by optimizing each separate objective function of the single-objective optimization problem to alleviate the computational complexity. Then, we propose a credit-based algorithm composed of a cyclic region growth algorithm and a region fine-tuning algorithm. The cyclic region growth algorithm finds an initial solution to the single-objective optimization problems set by a regional growth strategy with multiple restricts, whereas the region fine-tuning algorithm reallocates the tasks of the partitions with too many tasks to the partitions with too few tasks by constructing a search tree, thereby converging the initial solution to the optimal solution. Simulation results indicate that compared with conventional multi-robot complete coverage problem algorithms, the credit-based algorithm can obtain the optimal solution with the increased number of robots and enlarged size of the mission environment. |
| Related Links | https://journals.sagepub.com/doi/pdf/10.1177/17298806221091685?download=true |
| ISSN | 17298806 |
| Issue Number | 2 |
| Volume Number | 19 |
| Journal | International Journal of Advanced Robotic Systems (ARX) |
| e-ISSN | 17298814 |
| DOI | 10.1177/17298806221091685 |
| Language | English |
| Publisher | Sage Publications UK |
| Publisher Date | 2022-04-22 |
| Publisher Place | London |
| Access Restriction | Open |
| Rights Holder | © The Author(s) 2022 |
| Subject Keyword | Complete coverage problem multi-robot task allocation balanced connected task allocation |
| Content Type | Text |
| Resource Type | Article |
| Subject | Artificial Intelligence Computer Science Applications Software |
