Compression and Indexing Method for Data Acquisition Robots

Mobile robots possessing a number of sensors have limited storage space and battery power. In this paper, we propose a lossless compression scheme and an indexing method for storing and retrieving sensing data of the mobile robots acting at a disaster site. The probability‐based compression scheme, considering distribution range of the values to be compressed, is appropriate for a normal situation where sensing values are within a standard range. However, its efficiency can decrease significantly in an environment where the distribution range varies dynamically, resulting in a potential damage to the original data due to the lossy compression. The extended Elias gamma coding scheme proposed in this study does not cause loss of sensing data by compressing losslessly negative integers and real numbers as well as positive integers. The signature index structure based on the Elias gamma code stores and retrieves sensing data in the compressed form. An experiment is conducted to examine the performance of the proposed compression and indexing scheme.