Frontier Based Exploration for Autonomous Robot
This is an incremental improvement for autonomous robotics, addressing exploration in unknown environments.
The paper tackles autonomous robot exploration by implementing a Wavefront Frontier Detector (WFD) strategy, which enables robots to explore both large open and small cluttered spaces, with the map validated against a teleoperation package in Gazebo simulation and on a Kobuki TurtleBot using ROS.
Exploration is process of selecting target points that yield the biggest contribution to a specific gain function at an initially unknown environment. Frontier-based exploration is the most common approach to exploration, wherein frontiers are regions on the boundary between open space and unexplored space. By moving to a new frontier, we can keep building the map of the environment, until there are no new frontiers left to detect. In this paper, an autonomous frontier-based exploration strategy, namely Wavefront Frontier Detector (WFD) is described and implemented on Gazebo Simulation Environment as well as on hardware platform, i.e. Kobuki TurtleBot using Robot Operating System (ROS). The advantage of this algorithm is that the robot can explore large open spaces as well as small cluttered spaces. Further, the map generated from this technique is compared and validated with the map generated using turtlebot_teleop ROS Package.