Enhancing Robotic Communications via Mobility Diversity Algorithms

Nowadays wireless communications is an important aspect of mobile robotics. It is common that mobile robots need to establish wireless links to exchange information with other robots, base stations or sensor nodes. And, as in traditional mobile communications small-scale wireless channel fading also occurs in these scenarios. This phenomenon means that the channel gain will vary significantly over small-distances and in a random manner. This degrades both the communication ability of the robots and as a consequence, their overall performance in executing certain tasks. There is therefore a clear need to compensate for this small-scale fading. We could of course compensate small-scale fading in robotic communications using classical diversity techniques. But these diversity techniques were designed for transceivers that either cannot move, or can move but have no control over their position. In the context of robotic communications we can think of mobile robots as transceivers who know their own position and can also control it. This allows us to create a new form of diversity called mobility diversity whose principle is as follows. If the mobile robot experiences a poor channel gain due to a deep fading then it can alter its location by a small amount in order to find a new point with a higher channel gain (note that a low channel gain requires more transmitter energy to achieve the same SNR at the receiver as a high channel gain). Now, the more points the robot explores then the higher is the probability of obtaining a high channel gain but the consumption of mechanical energy also increases. Thus efficient mobility diversity algorithms (MDAs) must be able to deliver high channel gains while simultaneously using a small amount of mechanical energy. In this thesis, we start by simultaneously considering the theoretical aspects of both wireless communications and robotics that underpin this interdisciplinary problem. We then develop intelligent algorithms (MDAs) to solve the maximise channel gain/ minimise mechanical energy challenge while looking at various modifications that can occur i.e., predetermined and adaptive stopping points; MDAs for robots as wireless relays; MDAs that incorporate energy harvesting; and finally optimisation over a continuous search space. In summary, mobility diversity is a relatively new research area in an early stage of development. In this thesis we have developed a comprehensive theory for MDAs that will form the basis for future applications as outlined in chapter 7

Communications-Aware Robotics: Challenges and Opportunities

The use of Unmanned Ground Vehicles (UGVs) and Unmanned Aerial Vehicles (UAVs) has seen significant growth in the research community, industry, and society. Many of these agents are equipped with communication systems that are essential for completing certain tasks successfully. This has led to the emergence of a new interdisciplinary field at the intersection of robotics and communications, which has been further driven by the integration of UAVs into 5G and 6G communication networks. However, one of the main challenges in this research area is how many researchers tend to oversimplify either the robotics or the communications aspects, hindering the full potential of this new interdisciplinary field. In this paper, we present some of the necessary modeling tools for addressing these problems from both a robotics and communications perspective, using the UAV communications relay as an example.Comment: 6 pages, 4 figures, accepted for presentation to the 2023 International Conference on Unmanned Aircraft Systems (ICUAS) at Lazarski University, Warsaw, Polan

Energy Balancing for Robotic Aided Clustered Wireless Sensor Networks

We consider the problem of energy balancing in a clustered wireless sensor network (WSN) deployed randomly in a large field and aided by a mobile robot (MR). The sensor nodes (SNs) are tasked with monitoring a region of interest (ROI) and reporting their test statistics to the cluster heads (CHs), which they subsequently report to the fusion center (FC) over a wireless fading channel. To maximize the lifetime of the WSN, the MR is deployed to act as an adaptive relay between a subset of the CHs and the FC. To achieve this we develop a multipl

Energy balancing for robotic aided clustered wireless sensor networks using mobility diversity algorithms

We consider the problem of energy balancing in a clustered wireless sensor network (WSN) deployed randomly in a large field and aided by a mobile robot (MR). The sensor nodes (SNs) are tasked to monitor a region of interest (ROI) and report their test statistics to the cluster heads (CHs), which subsequently report to the fusion center (FC) over a wireless fading channel. To maximize the lifetime of the WSN, the MR is deployed to act as an adaptive relay between a subset of the CHs and the FC. To achieve this we develop a multiple−link mobility diversity algorithm (MDA) executed by the MR that will allow to compensate simultaneously for the small-scale fading at the established wireless links (i.e., the MR-to-FC as well as various CH-to-MR communication links). Simulation results show that the proposed MR aided technique is able to significantly reduce the transmission power required and thus extend the operational lifetime of the WSN. We also show how the effect of small-scale fading at various wireless links is mitigated by using the proposed multiple−link MDA executed by a MR equipped with a single antenna

Robotic Mobility Diversity Algorithm with Continuous Search Space

Small scale fading makes the wireless channel gain vary significantly over small distances and in the context of classical communication systems it can be detrimental to performance. But in the context of mobile robot (MR) wireless communications, we can take advantage of the fading using a mobility diversity algorithm (MDA) to deliberately locate the MR at a point where the channel gain is high. There are two classes of MDAs. In the first class, the MR explores various points, stops at each one to collect channel measurements and then locates the best position to establish communications. In the second class the MR moves, without stopping, along a continuous path while collecting channel measurements and then stops at the end of the path. It determines the best point to establish communications. Until now, the shape of the continuous path for such MDAs has been arbitrarily selected and currently there is no method to optimize it. In this paper, we propose a method to optimize such a path. Simulation results show that such optimized paths provide the MDAs with an increased performance, enabling them to experience higher channel gains while using less mechanical energy for the MR motion

MRS Drone: A Modular Platform for Real-World Deployment of Aerial Multi-Robot Systems

This paper presents a modular autonomous Unmanned Aerial Vehicle (UAV) platform called the Multi-robot Systems (MRS) Drone that can be used in a large range of indoor and outdoor applications. The MRS Drone features unique modularity with respect to changes in actuators, frames, and sensory configuration. As the name suggests, the platform is specially tailored for deployment within a MRS group. The MRS Drone contributes to the state-of-the-art of UAV platforms by allowing smooth real-world deployment of multiple aerial robots, as well as by outperforming other platforms with its modularity. For real-world multi-robot deployment in various applications, the platform is easy to both assemble and modify. Moreover, it is accompanied by a realistic simulator to enable safe pre-flight testing and a smooth transition to complex real-world experiments. In this manuscript, we present mechanical and electrical designs, software architecture, and technical specifications to build a fully autonomous multi UAV system. Finally, we demonstrate the full capabilities and the unique modularity of the MRS Drone in various real-world applications that required a diverse range of platform configurations.Comment: 49 pages, 39 figures, accepted for publication to the Journal of Intelligent & Robotic System

UAV Trajectory Planning for Delay Tolerant Communications

International audienceIn this paper, we address the problem of optimizing a communication-aware trajectory for a quadrotor that must transfer periodically (with fixed period T) a maximum amount of data from a source node (SN) to a destination node (DN). The communications aspect is mathematically stated by linking the bit rate to the channel capacity concept from information theory. The trajectory is optimized using a parametric approach using Fourier series in order to reduce the computational load of the optimization process. We show that the proposed trajectory results in a large increase of the amount of transferred data, and can be easily tracked by the quadrotor

UAV Trajectory Planning for Delay Tolerant Communications

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Optimum Trajectory Planning for Robotic Data Ferries in Delay Tolerant Wireless Sensor Networks

We consider the issue of energy efficient data collection in the context of a mobile robot-aided delay tolerant wireless sensor network (DTSN). The latter is composed of static nodes (SNs), a fusion center (FC) and a mobile robot (MR), which acts as a data ferry in order to reduce energy consumption at the SNs, thereby increasing their lifetime. The considered wireless channel model accounts for both path loss and shadowing. We propose a method to optimise the trajectory of the MR so as to minimise the overall energy consumption of the DTSN, while controlling the latency of the end-to-end transmission and maintaining the number of bits in the SNs' buffers bounded. Simulation results show the effectiveness of the proposed solution in reducing the energy consumption of the DTSN

Communication-aware energy efficient trajectory planning with limited channel knowledge

International audienceWireless communications is nowadays an important aspect of robotics. There are many applications in which a robot must move to a certain goal point while transmitting information through a wireless channel which depends on the particular trajectory chosen by the robot to reach the goal point. In this context, we develop a method to generate optimum trajectories which allow the robot to reach the goal point using little mechanical energy while transmitting as much data as possible. This is done by optimizing the trajectory (path and velocity profile) so that the robot consumes less energy while also offering good wireless channel conditions. We consider a realistic wireless channel model as well as a realistic dynamic model for the mobile robot (considered here to be a drone). Simulations results illustrate the merits of the proposed method