A new gain function for compact exploration

摘要

Trade-off between the information gain and cost has been extensively used as an evaluation criteria for target points in robot exploration strategies where the primary goal is to reduce the mission time. This article introduces a new gain function that has an integrated cost component that can be used in exploration strategies to map the terrain in a balanced way in all directions to generate compact maps. Article also presents an approach to efficiently calculate the gain values. Simulations in both low and high obstacle density environments for single and multi-robot exploration strategies indicate the utility of the new gain function in generating compact maps.