Multi-robot mapping
Informative path planning for multi-robot mapping with Sampling based optimisation
Abstract: Autonomous mobile robots have evolved over the past 2 decades and have the potential to change the way humans live and work. These robots can be made to work autonomously in a diverse set of environments ranging from offices and households to disaster sites and tough industrial environments. For autonomous robots to be fully functional, robots would have to maintain an internal description or a map of the environment to safely navigate through while carrying out the tasks they are designed for. The process of map building of an environment to extract relevant features is an integral process for many robotics applications. Conventionally, these maps are represented as discrete occupancy grids composed of cells that represent the presence of an obstacle at a given location in the environment. In most of these applications, an autonomous robot would have no prior information of the environment it is placed within. Therefore, such a robot is initially tasked to explore the environment to map features such as obstacles, walls and empty space. Thus, the primary objective of this project is to propose a new exploration strategy for building a map of an unknown environment. In the following section, we provide a summary and review some of the exploration algorithms in literature.
The paths planned by this approach:
