Networked Multi-robot Systems Research Articles

Wireless Networked Multirobot Systems in Smart Factories

Smart manufacturing based on artificial intelligence and information communication technology will become the main contributor to the digital economy of the upcoming decades. In order to execute flexible production, smart manufacturing must holistically integrate wireless networking, computing, and automatic control technologies. This article discusses the challenges of this complex system engineering from a wireless networking perspective. Starting from enabling flexible reconfiguration of a smart factory, we discuss existing wireless technology and the trends of wireless networking evolution to facilitate multirobot smart factories. Furthermore, the special sequential decision-making of a multirobot manufacturing system is examined. Social learning can be used to extend the resilience of precision operation in a multirobot system by taking network topology into consideration, which also introduces a new vision for the cybersecurity of smart factories. A summary of highlights of technological opportunities for holistic facilitation of wireless networked multirobot smart factories rounds off this article.

Distributed Artificial Neural Networks-Based Adaptive Strictly Negative Imaginary Formation Controllers for Unmanned Aerial Vehicles in Time-Varying Environments

Formation control techniques have been widely implemented in networked multirobot systems. In this article, we present a novel framework for swarm multiagent systems based on the relative-position output feedback consensus supported with the new concept of adaptive strictly negative imaginary consensus controllers, leveraging the learning capability of artificial neural networks. For experimental validation, we consider the case of two quadcopters moving together while carrying a dynamic load. We employ Kharitonov's theorem to study the stability of the proposed adaptive control systems. Finally, a rigorous real-time experimental study is conducted to highlight the merits of the proposed formation control algorithms.

Consensus in networked multi-robot systems via local state feedback robust control

In the article, the consensus problem is considered for networked multi-robot systems, in which the dynamical equation of all robots is non-holonomic and nonlinear systems. In the multi-robot systems, each robot updates its current states and receives the states from the neighboring robots. Under the assumption that if the network graph is bidirectional, a local information-based state feedback robust controller is designed to make sure the convergence of the individual robots’ states to a common value. Finally, the effectiveness of the presented method is illustrated by the simulation results of a group of four mobile robots.

Energy-efficient optimal task offloading in cloud networked multi-robot systems

Task offloading plays a critical role in cloud networked multi-robot systems for leveraging computation support from cloud infrastructure and benefiting greatly from the well-developed cloud network facilities. However, considering the delay constraint, the extra costs of data transmission and remote computation, it is not trivial to make optimized offloading decisions. In particular, task offloading for robots is more complex due to their on-demand mobility and network connectivity that significantly influence the robot–cloud communication links. Moreover, for multi-robot systems, a suitable balance of workload between local network (robot–robot) and global cloud (robot–cloud) is also required, so as to attain proper utilization of resources. Therefore, it is essential to establish more comprehensive offloading schemes for modeling systems that can handle these higher level of complications. With that view, this paper aims to develop a novel multi-layer decision-making scheme for task offloading which jointly considers the following four aspects: (i) selection of task for offloading, (ii) selection of robot to offload a task, (iii) selection of location to offload/perform task, (iv) selection of access point for offloaded task. An integrated framework for cloud networked multi-robot systems is presented to enable our task offloading scheme where the primary robot can aid from additional local robots to improve the offloading process. In particular, we consider a warehouse scenario with 36 cell workspace where a 40 node taskflow is motivated from a “parcel sorting and distribution” application, to be completed by the primary robot. The offloading decision for each task is formulated as part of a joint optimization problem and it is solved by developing a multi-layer genetic algorithm scheme that takes into account motion, network connectivity and local sharing for its offloading decisions. We evaluate the results of the scheme via comparison with two validated benchmarks. The outcome highlights a significant improvement in overall system performance due to joint involvement of motion (path planning), connectivity (bandwidth estimation) and robot–robot communication (local offloading) that facilitates energy-efficient offloading to cloud, faster completion of tasks and better utilization of available resources.

Hierarchical Distributed Control for Global Network Integrity Preservation in Multirobot Systems.

In this paper, we address a novel hierarchical distributed control (HDC) strategy for networked multirobot systems (MRSs). This strategy is developed on a geometric approach without requiring estimation of algebraic connectivity. It is originally based upon behavioral control, but upgraded by distributed node control with a mobility constraint for global network integrity preservation and distributed connectivity control with a local connectivity minimization strategy for network coverage expansion. Thanks to properties of HDC, a networked MRS is capable of achieving high performance with cooperative tasks. We have examined and evaluated our proposed method in both simulations with up to 100 simulated robots and real-world experiments with up to 14 real robots.

Group Regional Consensus of Networked Lagrangian Systems With Input Disturbances

Networked multirobot systems under the coordinated control can perform tasks more effectively than a group of individually operating robots. This paper studies the group regional consensus of networked multirobot systems (formulated by second-order Lagrangian dynamics) having input disturbances under directed acyclic topology. An adaptive control protocol is designed to achieve group regional consensus of the networked Lagrangian systems with parametric uncertainties for both leader and leaderless cases. Sufficient conditions are established to guarantee group regional consensus for any prior given desired consensus errors. Compared with the existing work, a distinctive feature of the proposed control algorithm is that the stability analysis indicates the global validity of the obtained consensus results. Numerical examples are provided to demonstrate the effectiveness of the proposed scheme.

Observer-Based Decentralized Fault Detection and Isolation Strategy for Networked Multirobot Systems

In this paper, we present a distributed fault detection and isolation (FDI) strategy for a team of networked robots that builds on a distributed controller–observer schema. Remarkably different from other works in literature, the proposed FDI approach makes each robot of the team able to detect and isolate faults occurring on other robots, even if they are not direct neighbors. By means of a local observer, each robot can estimate the overall state of the team and it can use such an estimate to compute its local control input to achieve global tasks. The same information used by the local observers is also used to compute residual vectors, whose aim is to allow the detection and the isolation of actuator faults occurring on any robot of the team. Adaptive thresholds are derived based on the dynamics of the residual vectors by considering the presence of nonzero initial observer estimation errors, and noise terms affecting state measurement and model dynamics. The approach is validated via both numerical simulations and experiments involving four Khepera III mobile robots.

Range‐only distributed navigation protocol for uniform coverage in wireless sensor networks

In this study, the authors propose a novel range-only distributed motion coordination to achieve square-grid blanket coverage for self-deployments of networked multi-robot systems. They specifically address the research question of maximising coverage and minimising local uniformity index (i.e. to achieve uniform coverage) for each sensor node while simultaneously maintaining the connectivity of the whole network in the absence of central coordinated controller. Under the umbrella of intelligent controls, the motion coordination scheme employed in this study is because of the nearest neighbour techniques which are employed for the purpose of clustering and autonomous coordination among sensor nodes in local area (vicinity), that is, to achieve distributed coverage. The author's research indicates that simple motion coordination schemes have led to intelligent ensemble behaviours at group levels. Compared to the existing algorithms, the superiorities of their decentralised protocol are because of its reliability and robustness against inevitable node failures, scalability and flexibility in the sense of the growth of the networks as well as its uniformity across most of steady-state positions of sensor nodes leading to better network management. They present extensive computer simulations to investigate the effectiveness of their proposed algorithm for self-deployment in challenging deployment regions.

RoboNetSim: An integrated framework for multi-robot and network simulation

In networked multi-robot systems, communication plays a major role defining system’s dynamics and performance. Unfortunately, existing multi-robot simulators do not provide advanced communication models. Therefore, given the intrinsic unreliability of wireless communications, significant differences might be observed between simulation and real-world results.Addressing these issues, we present RoboNetSim, an integrated simulation framework for communication-realistic simulation of networked multi-robot systems. RoboNetSim integrates multi-robot simulators with network simulators. We present two model implementations based on ARGoS at the robotic side, and NS-2 and NS-3 as network simulators. We evaluate the framework in terms of accuracy and computational performance, showing that it can efficiently simulate systems consisting of hundreds of robots.Using the Stage simulator as an example, we also show the integration of a robotic simulator with RoboNetSim by only adapting robot controllers, without the need to adapt the general code of the simulator.Finally, we demonstrate the effects of communication on mobile multi-robot systems. We consider two different case studies: a distributed coordination and task assignment scenario, and a coordinated mobility scenario. We compare realistic network simulation with simplified communication models and algorithms, and we study the resulting behavior and performance of the multi-robot system and the impact of different parameters.

Supporting Navigation in Multi-Robot Systems through Delay Tolerant Network Communication

In this paper we study a problem of navigation in networked multi-robot systems. The robots are deployed in a confined area, where they move around and solve tasks. They communicate with each other through an infrared communication device, so that an ad hoc network is formed among them. Due to the limited range and line of sight nature of the infrared communication, this network has intermittent connectivity. The question we address is how a particular robot can use this network to find a target location that is indicated by another robot (e.g., the other robot has identified a task to be serviced by the searching robot). All other robots are involved in tasks of their own, and do not change their movements to help the searching robot find its destination. However, they do offer support by forwarding messages over the network. We propose a new algorithm based on routing in ad hoc and delay tolerant networks that can run on the network formed between the robots and provide navigation information to the searching robot. We evaluate the validity of our approach both in simulation and through an implementation on a group of 16 e-puck robots.