Recent years have witnessed the prosperity of robots and in order to support consensus and cooperation for multi- robot system, wireless communications and networking among robots and the infrastructure have become indispensable. In this technical note, we first provide an overview of the research contributions on communication-aware motion planning (CAMP) in designing wireless-connected robotic networks (WCRNs), where the degree-of-freedom (DoF) provided by motion and communication capabilities embraced by the robots have not been fully exploited. Therefore, we propose the framework of joint communication-motion planning (JCMP) as well as the architecture for incorporating JCMP in WCRNs. The proposed architecture is motivated by the observe-orient-decision-action (OODA) model commonly adopted in robotic motion control and cognitive radio. Then, we provide an overview of the orient module that quantify the connectivity assessment. Afterwards, we highlight the JCMP module and compare it with the conventional communication-planning, where the necessity of the JCMP is validated via both theoretical analysis and simulation results of an illustrative example. Finally, a series of open problems are discussed, which picture the gap between the state-of-the-art and a practical WCRN.
Recent years have witnessed the evolution of robotics and great industrial academic efforts. As the robots interact with the physical and social environments, considerable research contributions have been devoted to robotic sensing, cognition, motion path planning and control @cite_37 . A multi-robot system aims at achieving challenging tasks or significantly improving mission performance compared with a single robot, which demands consensus and cooperation among robots @cite_11 . Therefore, maintaining the connectivity quality for information exchange among robots becomes vital. As mobile robots are less likely to be connected via wires, the wireless communications and networking among robots and the infrastructure would play an crucial role and the wireless-connected robotic networks (WCRNs) are very likely to be incorporated into the next-generation communication networks.
@cite_37 @cite_11
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Although human-multi-robot systems have received increased attention in recent years, current implementations rely on structured environments and utilize specialized, research-grade hardware to operate. This letter presents approaches that leverage the visual and inertial sensing of mobile devices to address the estimation and control challenges of multi-robot systems that function in shared spaces with human operators such that both the mobile device camera and robots can move freely in the environment. It is shown that a subset of robots in the system can be used to maintain a reference frame that facilitates tracking and control of the remaining robots to perform tasks, such as object retrieval, using an operator's mobile device as the only sensing and computational platform in the system. To evaluate the performance of the proposed approaches, experiments are conducted in which a system of mobile robots is commanded to retrieve objects in an environment. Results show that, compared to using the visual data alone, integrating both the visual and inertial data from mobile devices yields improvements in performance, flexibility, and computational efficiency in implementing human-multi-robot systems. Planning under uncertainty faces a scalability problem when considering multi-robot teams, as the information space scales exponentially with the number of robots. To address this issue, this paper proposes to decentralize multi-robot partially observable Markov decision processes (POMDPs) while maintaining cooperation between robots by using POMDP policy auctions. Auctions provide a flexible way of coordinating individual policies modeled by POMDPs and have low communication requirements. In addition, communication models in the multi-agent POMDP literature severely mismatch with real inter-robot communication. We address this issue by exploiting a decentralized data fusion method in order to efficiently maintain a joint belief state among the robots. The paper presents two different applications: environmental monitoring with unmanned aerial vehicles (UAVs); and cooperative tracking, in which several robots have to jointly track a moving target of interest. The first one is used as a proof of concept and illustrates the proposed ideas through different simulations. The second one adds real multi-robot experiments, showcasing the flexibility and robust coordination that our techniques can provide. The deployment of multiple robots for achieving a common goal helps to improve the performance, efficiency, and or robustness in a variety of tasks. In particular, the observation of moving targets is an important multirobot application that still exhibits numerous open challenges, including the effective coordination of the robots. This paper reviews control techniques for cooperative mobile robots monitoring multiple targets. The simultaneous movement of robots and targets makes this problem particularly interesting, and our review systematically addresses this cooperative multirobot problem for the first time. We classify and critically discuss the control techniques: cooperative multirobot observation of multiple moving targets, cooperative search, acquisition, and track, cooperative tracking, and multirobot pursuit evasion. We also identify the five major elements that characterize this problem, namely, the coordination method, the environment, the target, the robot and its sensor(s). These elements are used to systematically analyze the control techniques. The majority of the studied work is based on simulation and laboratory studies, which may not accurately reflect real-world operational conditions. Importantly, while our systematic analysis is focused on multitarget observation, our proposed classification is useful also for related multirobot applications. To accomplish cooperative tasks, robotic systems are often required to communicate with each other. Thus, maintaining connectivity of the communication graph is a fundamental issue in the field of multi-robot systems. In this paper we present a completely decentralized control strategy for global connectivity maintenance of the communication graph. Considering the disk communication model, we describe a gradient-based control strategy that exploits decentralized estimation of the algebraic connectivity. Unlike previous approaches available in the literature, the proposed control algorithm solves the global connectivity problem in a decentralized manner providing theoretical guarantees, without requiring maintenance of the local connectivity between robotic systems. Moreover, results obtained with simulations and experiments on real robots are described for demonstrating the efficacy of the proposed algorithm.