Integrating robots into cellular networks creating connected robotic users has emerged as a promising technology for future smart cities and smart factories due to their low cost and high maneuverability. However, the requirement of establishing stable and high-quality communication links to the robotic users greatly restricts their applicability, especially in indoor environments where obstacles may block the wireless link. To tackle this challenge, in this paper, an indoor robot navigation system is investigated, where an intelligent reflecting surface (IRS) is employed to enhance the connectivity between the access point (AP) and robotic users. Both single-user and multiple-user scenarios are considered. In the single-user scenario, one mobile robotic user (MRU) communicates with the AP. In the multiple-user scenario, the AP serves one MRU and one static robotic user (SRU) employing either non-orthogonal multiple access (NOMA) or orthogonal multiple access (OMA) transmission. The considered system is optimized for minimization of the travelling time/distance of the MRU from a given starting point to a predefined final location, while satisfying constraints on the communication quality of the robotic users. To this end, a radio map based approach is proposed to exploit location-dependent channel propagation knowledge. For the single-user scenario, a channel power gain map is constructed, which characterizes the spatial distribution of the maximum expected effective channel power gain of the MRU for the optimal IRS phase shifts. Based on the obtained channel power gain map, the communication-aware robot path planing problem is solved by exploiting graph theory. For the multiple-user scenario, a communication rate map is constructed, which characterizes the spatial distribution of the maximum expected rate of the MRU for the optimal power allocation at the AP and the optimal IRS phase shifts subject to a minimum rate requirement for the SRU. The joint optimization problem is efficiently solved by invoking bisection search and successive convex approximation methods. Then, a graph theory based solution for the robot path planning problem is derived by exploiting the obtained communication rate map. Our numerical results show that: 1) the required travelling distance of the MRU can be significantly reduced by deploying an IRS; 2) NOMA yields a higher communication rate for the MRU than OMA; 3) the IRS performance gain is significantly more pronounced for NOMA than for OMA.

中文翻译：

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智能反射面增强型室内机器人路径规划：一种基于无线电地图的方法

由于其低成本和高机动性，将机器人集成到蜂窝网络中创建连接的机器人用户已成为未来智能城市和智能工厂的一项有前途的技术。然而，与机器人用户建立稳定和高质量的通信链路的要求极大地限制了它们的适用性，尤其是在障碍物可能阻挡无线链路的室内环境中。为了应对这一挑战，本文研究了一种室内机器人导航系统，其中采用智能反射面 (IRS) 来增强接入点 (AP) 和机器人用户之间的连接性。考虑了单用户和多用户场景。在单用户场景中，一个移动机器人用户 (MRU) 与 AP 通信。在多用户场景中，AP 服务于一个 MRU 和一个静态机器人用户 (SRU)，采用非正交多址 (NOMA) 或正交多址 (OMA) 传输。所考虑的系统经过优化，以最小化 MRU 从给定起点到预定最终位置的行进时间/距离，同时满足对机器人用户通信质量的约束。为此，一提出了基于无线电地图的方法来利用与位置相关的信道传播知识。对于单用户场景，一个构建了信道功率增益图，它表征了 MRU 的最大预期有效信道功率增益的空间分布，以获得最佳 IRS 相移。基于获得的信道功率增益图，利用图论解决了通信感知机器人路径规划问题。对于多用户场景，一个构建了通信速率图，它表征了在 AP 处进行最佳功率分配的 MRU 最大预期速率的空间分布，以及在 SRU 的最小速率要求下的最佳 IRS 相移。通过调用二分搜索和连续凸逼近方法可以有效地解决联合优化问题。然后，通过利用获得的通信速率图导出机器人路径规划问题的基于图论的解决方案。我们的数值结果表明：1) 部署 IRS 可以显着减少 MRU 所需的行驶距离；2) NOMA 为 MRU 提供比 OMA 更高的通信速率；3) 与 OMA 相比，NOMA 的 IRS 性能增益明显更明显。