Power Optimization in Mobile Robots Using a Real-Time Heuristic

Abstract

Mobile robots typically run using finite energy resources, supplied by finite batteries. The limitation of energy resources requires human intervention for recharging the batteries. To reduce human intervention, this work focuses on coordinating power in a group of robots. A power optimization subroutine provides some sense of distribution of power by the control unit (CU). A variety of on-board sensors, actuators, and communication modules are controlled by a heuristic-based controller class allowing such components to conserve the current taken from the attached power source. Using the proposed approach, autonomous robots will be aware of their power system, especially regarding battery life. The new approach takes advantage of a heuristic function which uses evaluation values calculated at different times for the different robots. An experimental setup is applied on the team of robots. The optimization module is evaluated on each robot. The results show that the team of mobile robots consumes less energy and more efficient power regulation during their duties. Finally, the application of the proposed optimization technique in a distributed manner achieves good power saving figures when performing the particular task.

Immersive Robotic Telepresence for Remote Educational Scenarios

“…Therefore, it is necessary to first identify and estimate the power consumption of the platform's various hardware components. Subsequently, the power associated with software applications needs to be modeled, since different heuristics would produce other levels of power consumption [29].…”

“…During the experiments, we observed that a demo is highly dependent on depth information or detection services, which constitute the robot's baseline energy consumption. In addition, in light of the economic aspects discussed in the following section, it is advisable to address sustainability issues already when designing demonstration routines [29].…”

Robust ℋ∞-Fuzzy Logic Control for Enhanced Tracking Performance of a Wheeled Mobile Robot in the Presence of Uncertain Nonlinear Perturbations

“…for σ = 0 (38) where σ = β(e 2 ) = υ r − e 2 for e 2 = 0 0 for e 2 = 0 (39) and α 0 (σ) follows from Equation (20).…”

“…While much effort has been devoted to energy modelling, power conservation, and optimization techniques [38,39] for precise tracking of WMRs, to the best of the author's knowledge, there has been to date little or no attention given towards investigating the effects of the power supply variation on the model's parameters. The main contribution of this work is on enhancing the tracking performance of a WMR, which is driven by two DC motors that are subject to structural model errors that are induced by time-varying power supply as well as behaviour of motions and motor speed.…”

Energy Efficiency of Force-Sensor-Controlled Humanoid-Robot Walking on Indoor Surfaces

“…Table 2 summarizes the battery-discharging times until the voltage drops to 8.5 V for both hard and soft surfaces, the three walking speeds and the still-standing condition. The measured battery-discharge time [30] is expressed in the form…”