In this paper, we consider the motion energy minimization problem for a robot that uses millimeter-wave (mm-wave) communications assisted by an intelligent reflective surface (IRS). The robot must perform tasks within given deadlines and it is subject to uplink quality of service (QoS) constraints. This problem is crucial for fully automated factories that are governed by the binomial of autonomous robots and new generations of mobile communications, i.e., 5G and 6G. In this new context, robot energy efficiency and communication reliability remain fundamental problems that couple in optimizing robot trajectory and communication QoS. More precisely, to account for the mutual dependency between robot position and communication QoS, robot trajectory and beamforming at the IRS and access point all need to be optimized. We present a solution that can decouple the two problems by exploiting mm-wave channel characteristics. Then, a closed-form solution is obtained for the beamforming optimization problem, whereas the trajectory is optimized by a novel successive-convex optimization-based algorithm that can deal with abrupt line-of-sight (LOS) to non-line-of-sight (NLOS) transitions. Specifically, the algorithm uses a radio map to avoid collisions with obstacles and poorly covered areas. We prove that the algorithm can converge to a solution satisfying the Karush-Kuhn-Tucker conditions. The simulation results show a fast convergence rate of the algorithm and a dramatic reduction of the motion energy consumption with respect to methods that aim to find maximum-rate trajectories. Moreover, we show that the use of passive IRSs represents a powerful solution to improve the radio coverage and motion energy efficiency of robots.
翻译:在本文中,我们考虑的是,对于使用智能反射表面(IRS)的机器人来说,运动节能最小化是运动能量最小化的问题。机器人必须在规定的期限内执行任务,并受制于服务质量(QOS)的限制。对于由自主机器人和新一代移动通信(即5G和6G)的二进制管理的完全自动化工厂来说,这个问题至关重要。在这一新的背景下,机器人能源效率和通信可靠性仍然是根本问题,在优化机器人轨迹和通信QosS的智能反射器方面,机器人节能和通信同步。更准确地说,要说明机器人位置和通信范围之间的相互依存性。机器人轨道必须在给定的最后期限内执行任务,并且要在IRS和接入点进行成型。我们提出了一个解决方案,通过利用毫米频道特性(即5G和6G)和新一代移动通信(即5G和6G)的二进制。在这个新背景下,机器人节能效率和通信可靠性仍然是最优化,而轨迹则由新型的螺旋优化优化算法来应对快速直线观察(LOS) 和机器人运行轨迹(LOS)的轨迹轨迹的轨迹,我们可以用不甚甚甚高的电压方法来显示快速的电压的电压-电压-电压-电压-电压-电路压-电路压-电路路压-电算法的节压效率。