Abstract:
The energy capacity of the batteries used as the main power source in mobile robotic devices determines the autonomous operation of the robot. To plan the execution of tasks by a group of robotic tools in terms of time consumption, it is important to take into account the time during which the battery of each individual robot is charged. When using wireless power transfer, this time depends on the efficiency of the power transfer system, on the power of the transferring part of the system, as well as on the level of charge required to recharge. In this paper, we propose a method for estimating the time of transfer of energy resources between two robots, taking into account these parameters. The proposed method takes into account the application of the algorithm for the final positioning of robots, the assessment of linear offsets between robots, includes the calculation of efficiency, as well as the determination of the battery charge time, taking into account the parameters obtained at the previous stages of the method. The final positioning algorithm for robots uses algorithms for processing data from a robot vision system to search for fiducial markers and determine their spatial characteristics to ensure the final positioning of mobile robotic platforms. These characteristics are also used to determine the linear offsets between robots, on which the efficiency of energy transfer depends. To determine it, the method uses a mathematical model of the energy characteristics of the wireless power transfer system and the obtained linear offsets. At the last stage of the method, the time for charging the battery of the mobile robot is calculated, taking into account the data from the previous stages. Application of the proposed method to simulate the positioning of robots in a certain set of points in the working space will reduce the time spent on charging the robot battery when using wireless power transfer. As a result of the simulation, it was determined that the transfer of energy resources between robots took place with an efficiency in the range from 58.11% to 68.22%, and out of 14 positioning points, 3 were identified with the shortest energy transfer time.
Keywords:mobile robotics, wireless power transfer, energy transfer time estimation, positioning of mobile robots, computer vision, ArUco marker.