Planning of Covering and Mine Sweeping Operations for Multiple Robots in Unknown Environments

In parallel with advances in robots hardware, the motion planning science has become increasingly indispensable and complicated, and enables robots to enhance their capabilities in applications where the presence of humans is impractical or hazardous. The covering and minesweeping operations of outdoor areas are examples of such applications. This paper deals with the problem of covering and minesweeping of unknown environments by multiple mobile robots which have cooperative interactions. For searching the space, the new method of multi sensor-based random trees (MSRT) is developed, and for planning the robots’ paths toward the scattered items and their collection, a mathematical model similar to the multiple traveling salesman problem is proposed, which together with the k-means clustering, the A* search, and the visibility graph techniques plans the route of each robot. Comparisons with the counterpart mathematic model solved to optimality showed that the proposed method produces suboptimal solutions in much shorter computational times.