This paper describes the construction of a 3D map of an indoor environment using the RGB-D camera (Microsoft Kinect V2.0). 3D mapping and localization have always been an intriguing topic in research and with the introduction of Microsoft Kinect sensor, the research has grown rapidly. In this paper, we propose a method to generate the 3D map of an indoor environment using the Microsoft Kinect version 2.0 sensor. The results obtained show an improvement over the previously used methods. We believe that this would contribute to many applications such as computer vision, robotics, home automation etc.

The exploration of premium and new locations is regarded as a fundamental function of every evolutionary algorithm. This is achieved using the crossover and mutation stages of the differential evolution (DE) method. A best-and-worst position-guided novel exploration approach for the DE algorithm is provided in this study. The proposed version, known as “Improved DE with Best and Worst positions (IDEBW)”, offers a more advantageous alternative for exploring new locations, either proceeding directly towards the best location or evacuating the worst location. The performance of the proposed IDEBW is investigated and compared with other DE variants and meta-heuristics algorithms based on 42 benchmark functions, including 13 classical and 29 non-traditional IEEE CEC-2017 test functions and 3 real-life applications of the IEEE CEC-2011 test suite. The results prove that the proposed approach successfully completes its task and makes the DE algorithm more efficient.