The Implementation of Hexagonal Robot Mapping and Positioning System Focuses on Environmental Scanning and Temperature Monitoring

Abstract

Various researches in the field of robotics have made great progress in developing methods to effectively determine the position of robots in unknown environments. The simultaneous localization and mapping (SLAM) task make determining the current position of the robot and performing path mapping possible. In this mapping, solid elements (landmarks) existing in the actual environment are even detected, which indicate that the direction of the robot changes during walking. This scheme provides the implementation analysis of the probabilistic particle filter method, which ensures the correct performance in the controlled actual scene under specific conditions, obtains the non-network connection environment information by storing the data in the temperature value sampling in the CVS file, and monitors the temperature measurement by displaying the heat map. Successful analysis must ensure the robustness of the results obtained when implementing these systems and take into account the feasibility of applying this work to the proposed objectivesd.