Collaborative Multi-Robot Exploration

In this paper we consider the problem of exploring an unknown environment by a team of robots. As in single-robot exploration the goal is to minimize the overall exploration time. The key problem to be solved therefore is to choose appropriate target points for the individual robots so that they simultaneously explore different regions of their environment. We present a probabilistic approach for the coordination of multiple robots which, in contrast to previous approaches, simultaneously takes into account the costs of reaching a target point and the utility of target points. The utility of target points is given by the size of the unexplored area that a robot can cover with its sensors upon reaching a target position. Whenever a target point is assigned to a specific robot, the utility of the unexplored area visible from this target position is reduced for the other robots. This way, a team of multiple robots assigns different target points to the individual robots. The technique has been implemented and tested extensively in real-world experiments and simulation runs. The results given in this paper demonstrate that our coordination technique significantly reduces the exploration time compared to previous approaches.

Authors

• Wolfram Burgard
• Mark Moors
• Dieter Fox
• Reid G. Simmons
• Sebastian Thrun

Keywords

• Collaboration
• Robot kinematics
• Robot sensing systems
• Computer science
• Costs
• Mobile robots
• Multirobot systems
• Testing
• Traveling salesman problems
• Redundancy
• Multi-robot Exploration
• Target Location
• Exploration Time
• Swarm Robotics
• Multiple Robots
• Individual Robots
• Advantage Of This Approach
• Simulation Experiments
• Grid Cells
• Global Map
• Exploration Process
• Individual Maps
• Straight-line Distance
• Value Iteration
• Position Of The Robot
• Exploration Of Environment
• Laser Ranging
• Real Robot
• Goal Position
• Robotic Group
• Single Robot