Balancing task allocation in multi-robot systems using K-means clustering and auction based mechanisms

► We model multi-robot task allocation problem which maximize utilization and minimize the travel cost. ► We propose a methodology for the real time (NP Hard) multi-robot task allocation problem which includes clustering and auction based mechanism. ► Our methodology reduces computational complexity and provides better solution quality. ► Our analysis suggests practitioners to select appropriate number of task clusters based on silhouette values and balancing ratio.