Cooperative Problem Research Articles

An improved variable neighborhood search algorithm embedded temporal and spatial synchronization for vehicle and drone cooperative routing problem with pre-reconnaissance

Drones are increasingly utilized for transportation reconnaissance due to their expansive field of view, cost-effectiveness, and agility. They can pre-reconnaissance the traveling routes of the ground vehicles carrying valuable goods to ensure the safety of vehicles and their goods. This rises a novel routing problem for the Vehicles and their Pre-Reconnaissance Drones, which is an integrated point and arc routing problem with temporal and spatial synchronization. A mixed integer linear programming model is developed to formulate the problem with complex synchronization constraints. The Variable Neighborhood Search algorithm integrated with the Temporal & Spatial synchronization-based Greedy search and simulated annealing strategy is designed to solve the model. A practical case based on real urban data from Beijing, China, and random instances with different sizes are tested and compared with the proposed algorithm. Computational results indicated that the proposed algorithm can solve the problem efficiently and outperform the simulated annealing algorithm and the greedy algorithm.

A learning-based memetic algorithm for a cooperative task allocation problem of multiple unmanned aerial vehicles in smart agriculture

Smart agriculture aligns with the principles of sustainable development, making it a crucial direction for the future agriculture. This study focuses on a cooperative plant protection task allocation problem (CPPTAP) of multiple unmanned aerial vehicles (UAVs) with a common deadline in smart agriculture. CPPTAP permits multiple UAVs to conduct pesticide spraying on the same field. The completion time for each task fluctuates due to the cooperation among UAVs. We present a mathematical model and learning-based memetic algorithm (L-MA) to maximize the total area of the fields to be sprayed. In the evolutionary stage, mutation and repair operators based on value information are applied to balance the exploration and exploitation, while a problem-specific local search strategy is designed to enhance exploitation capability. A knowledge-based UAV allocation method (KUAM) is employed to maximize UAV utilization efficiency and minimize conflicts. Throughout the search process, Q-learning is utilized to assist the aforementioned operators and make decisions on the number of cooperative UAVs on fields. The effectiveness of L-MA is validated by comparing it against other state-of-the-art algorithms. The results demonstrate that L-MA outperforms the compared algorithms at a considerable margin in a statistical sense.

Self‐organizing cooperative hunting for unmanned surface vehicles with constrained kinematics

SummaryThe article aims at solving a cooperative hunting problem for multiple unmanned surface vehicles (USVs) subject to constrained kinematics. In order to cooperatively trap the evader into the hunting domain, a velocity model with control variable for the pursuers is firstly proposed according to the Apollonius circle. Then, a flexible self‐organizing control strategy is developed, which enables the pursuers to approach the evader while forming an encirclement. The pursuers can dynamically adapt their strategies in real‐time by choosing the optimal control variable. Additionally, take into account the limitation imposed on the vessel's motion, the optimal control variable with constraint can be obtained by using the particle swarm optimization with log‐barrier method. The simulation results ultimately demonstrate the validity and superiority of the proposed cooperative hunting algorithm.

Attitude collaborative control strategy for space gravitational wave detection

This paper proposes a high-precision attitude cooperative control strategy for three spacecraft in space gravitational wave detection. Firstly, based on the layout of optical components on the spacecraft and factors such as external interference and model uncertainty, a relative attitude model based on the Euler angle is constructed for the characteristics of small angle motion in differential wavefront sensing mode. Secondly, aiming at the cooperative control problem of multi drag-free attitude control system after the laser link capture between two spacecraft is completed, an attitude control method based on consensus mode cooperative control strategy is proposed. It combines local neighbourhood error from star sensing and differential wavefront sensing with an adaptive controller for equilateral triangle configuration control. Additionally, a cooperative control strategy based on laser measurement information is established to improve control accuracy by avoiding star sensors with low accuracy. Simulation results indicate that the control accuracy of the consistency mode and its sub-mode laser measurement mode is superior to the master-slave and cyclic modes, achieving better than 5×10−6 rad. The laser measurement mode demonstrates the highest accuracy, with relative attitude control accuracy reaching 1.5×10−7 rad, meeting the requirements for space gravitational wave detection.

Neuroadaptive Cooperative Fault-Tolerant Control of Heterogeneous Multiagent Systems Based on Fully Actuated System Approaches.

The leader-following cooperative problem in heterogeneous multiagent systems (HMASs) with unmodeled dynamics and actuator faults is investigated in this article. The HMASs, which include unmanned ground vehicles and unmanned aerial vehicles, are first described using a fully actuated system model (FASM). The FASM, as opposed to the first-order state-space model, preserves the physical significance of original systems and makes it feasible to apply the control rule entirely. In order to approximate unknown system dynamics, novel neuroadaptive laws with few learning parameters are then suggested. To counteract the negative effects of actuator faults, the Nussbaum function and adaptive approach are utilized. In addition, a cooperative fault-tolerant protocol is suggested, wherein consensus errors are uniformly ultimately bounded. The lack of virtual control variables in the proposed protocol reduces its complexity. The theoretical results are then validated by numerical simulations.

Application of improved grey wolf model in collaborative trajectory optimization of unmanned aerial vehicle swarm

With the development of science and technology and economy, UAV is used more and more widely. However, the existing UAV trajectory planning methods have the limitations of high cost and low intelligence. In view of this, grey Wolf algorithm is being used to achieve collaborative trajectory optimization of UAV groups. However, it is found that the Grey Wolf optimization algorithm (GWO) has the problem of weak cooperation. In this study, based on the traditional GWO pheromone factor is introduced to improve it.. Aiming at the problem of unstable performance of swarm intelligence optimization algorithm under dynamic threat, deep reinforcement learning is used to optimize the model. An unmanned aerial vehicle swarm trajectory planning model was constructed based on the improved grey wolf algorithm. Through experimental analysis, the optimal fitness value of the improved grey wolf algorithm was lower than 0.43 of the grey wolf algorithm. Compared with other algorithms, the fitness value of this algorithm is significantly reduced and the stability is higher. In complex scenarios, the improved grey wolf algorithm had a trajectory length of 70.51 km and a planning time of 5.92 s, which was clearly superior to other algorithms. The path length planned by the research and design model was 58.476 km, which was significantly smaller than the other three models. The planning time was 5.33 s and the number of path extension points was 46. The indicator values of the Unmanned Aerial Vehicle swarm trajectory planning model designed by this research were all smaller than the other three models. By analyzing the results, the model can achieve low-cost trajectory optimization, providing more reasonable technical support for unmanned aerial vehicle mission execution.

Leader-Following Connectivity Preservation and Collision Avoidance Control for Multiple Spacecraft with Bounded Actuation

This paper investigates the distributed formation control of a group of leader-following spacecraft with bounded actuation and limited communication ranges. In particular, connectivity-preserving and collision-avoidance controllers are proposed for the leader with constant or time-varying velocity, respectively. The communication graph between the spacecraft is modeled via a distance-induced proximity graph. By designing a virtual proxy for each spacecraft, the spacecraft–proxy couplings address the actuator saturation constraints. The inter-proxy dynamics incorporated with a bounded artificial potential function fulfill the coordination of all proxies. In addition, the bounded potential function can simultaneously tackle connectivity preservation and collision avoidance problems. The distributed formation controllers are proposed for multiple spacecraft with constant or time-varying velocities relative to the leader. A sliding mode control approach and the proxies’ dynamics are used in the design of a distributed cooperative controller for spacecraft to address the cooperative problem between the followers and the leader. Numerical simulations confirm the effectiveness of the anti-saturation distributed connectivity preservation controller.

Agricultural Vertical Cooperatives: the State and Directions of State Support

Agricultural vertical cooperatives created by small agricultural producers play an essential role in the market integration of small farms, ensuring employment and income of the rural population, and the stability of the agro-food market. The study of the problems of rural cooperation belongs to the relevant areas of economic research in the agro-industrial complex. The article analyzes the level and trends in the development of agricultural vertical cooperatives in Russia, including the dynamics of the number of certain types of cooperatives in 2019-2024, the social composition and equipment of fixed assets of cooperatives, their role in the production of a number of food resources. The conclusion is made about the slow development of cooperation and the significant differentiation of the cooperative movement across the subjects of the Russian Federation. The main reasons for the current situation and directions for improving cooperative policy in rural areas are considered.

Collaborative Pricing Strategy of Distribution Network and Electric Vehicle Aggregator Based on Integral System

Scaled EVs as a new type of load have great potential to participate in the standby market. However, the uncertainty of EV users' participation in aggregator regulation affects the optimal strategy for aggregators to participate in the market. Aiming at the uncertainty of users' willingness and the conflict of interest between aggregators and the distribution network, this paper proposes an optimal scheduling strategy of master-slave game for EV aggregators to improve users' willingness with a point system. First, the second-order cone optimal current model of the distribution network is established, and then the distribution network node marginal tariff is obtained. Second, the aggregator revenue model with energy storage is established, and the price-guided demand response model is proposed, while the aggregator point system is established to guide the charging behavior of EV users, so that the cooperative operation optimization problem between the distribution grid and the aggregator can be solved, and the economic interests among EV users, EV aggregators and distribution grid operators can be effectively balanced.

ПРАВОВОЕ РЕГУЛИРОВАНИЕ СПАСАНИЯ ЛЮДЕЙ НА ВОДНЫХ ОБЪЕКТАХ В АРКТИЧЕСКОЙ ЗОНЕ (ОБЗОР МАТЕРИАЛОВ «КРУГЛОГО СТОЛА»)

The review highlights the abstracts of the round table «Legal regulation of human rescue on water bodies in the Arctic zone», held on February 7, 2024 at the Federal state budgetary institution Arctic rescue educational and scientific center «Vytegra» (Vologda region, Vytegorsky district, Ustye village) within the framework of the International Scientific and practical conference «Russian ice – 2024». 10 scientific and educational organizations, more than 50 participants were represented. The review highlights the problems and prospects of the legislation of the Russian Federation in the field of search and rescue of people in the waters of the Arctic basin; problems of interdepartmental cooperation in the development of a system for providing search and rescue of people at sea in the Arctic zone: historical experience of conducting marine rescue operations in the Arctic, etc.

A study on dual quaternion based cooperative relative navigation of multiple UAVs with monocular vision-inertial integration

This paper addresses a cooperative relative navigation problem for multiple aerial agents, relying on visual tracking information between vehicles. The research aims to investigate a sensor fusion architecture and algorithm that leverages partially available absolute navigation knowledge while exploiting collaborative visual interaction between vehicles in mission flight areas, where satellite navigation-denied regions are irregularly located. To achieve this, the paper introduces a new approach to defining the relative poses of cameras and develops a corresponding process to secure the relative pose information. This contrasts with previous research, which simply linearized the relative pose information of aircraft cameras into navigation states defined in an absolute coordinate system. Specifically, the target pose in relative navigation is defined, and the pose of the camera and feature points are directly derived using dual quaternion representation, which compactly represents both translation and rotation. Furthermore, a mathematical model for the relative pose of the camera is derived through the dual quaternion framework, enabling an explicit pose formulation of relative navigation. The study investigates navigation performance in typical mission flight scenarios using an in-house high-fidelity simulator and quantitatively highlights the contributions of the proposed scheme by comparing the navigation error performance. Consequently, the proposed method demonstrates to have navigation accuracy in decimeter level even in GNSS-denied environments and an improved 3D Root Mean Square (RMS) error by 30% smaller than the conventional absolute navigation framework.

Observer‐based fixed‐time task‐space cooperative tracking control of networked Lagrangian agents with quantized communication

AbstractIn this article, the task‐space cooperative tracking control (TSCTC) problem of networked Lagrangian agents (NLAs) with quantized communication is investigated in fixed time, where every Lagrangian agent suffers from imprecise dynamics and external disturbances. A hierarchical observer‐based fixed‐time control (HOBFTC) algorithm is proposed, where there are four parts: a prescribed‐time input observer is proposed to recover the unknown input of the leader, a distributed estimator control is designed to force the estimated values to converge the states (position and velocity) of the leader, a fixed‐time disturbance observer is presented to recover the total disturbances of NLAs, and a nonsingular fixed‐time local control is given to guarantee that the task‐space cooperative tracking can be achieved. The salient features are twofold: (1) by employing the hierarchical control strategy, the proposed control algorithm is clearly structured to solve the complex cooperative tracking problem with multiple constraints including quantized communication, imprecise dynamics and external disturbances. (2) the convergence time of the proposed control algorithm can be set freely by selecting some parameters, which are independent of the initial conditions. Some sufficient conditions are obtained and some simulation examples are given to validate the effectiveness of the proposed algorithm.

Embedded technique-based formation control of multiple wheeled mobile robots with application to cooperative transportation

The cooperative transportation problem for multiple wheeled mobile robots (WMRs) via formation control is investigated in this paper. A formation control algorithm based on an embedded technique is proposed for cooperative transportation of a shared object using n-WMRs. Instead of relying on the conventional design philosophy directly based on formation errors, the proposed algorithm is divided into two parts by considering the communication topology and WMRs’ dynamics “separately”. The first part involves a distributed signal generator that generates desired trajectories for the WMRs based on their initial positions, the formation vector, and the desired trajectory of the object. The second part consists of tracking controllers to enable the WMRs to track their desired trajectories. The proposed algorithm is distributed and differs from the existing cooperative transportation algorithms, as it eliminates the requirement for all WMRs to know the object’s position. Moreover, it exhibits remarkable compatibility and features a concise modular design. With the proposed algorithm, WMRs achieve formation in finite time. Theoretical proof supports the effectiveness of the proposed algorithm, which is further validated through several conducted experiments.

Cooperative output regulation of heterogeneous multi‐agent systems under false data injection attacks

AbstractThis paper studies the cooperative output regulation problem for heterogeneous multi‐agent systems (MASs) subject to false data injection (FDI) attacks, which means the malicious cyber‐attackers may inject false data into the communication topology randomly. To ensure that each follower agent can track the leader agent accurately, we construct both an observer and a control law for each follower agent. Since the FDI attacks may exist in the communication network, a filter with an adaptive compensator, which can estimate attack signals dynamically, is equipped for each observer, such that the filter can neutralize attacks when malicious attackers launch attacks. Therefore, the cooperative output regulation can be achieved under the control law based on the observer no matter whether there exist attacks or not. Finally, a numerical example is provided for validating the theoretical results.

Adaptive large neighborhood search algorithm with reinforcement search strategy for solving extended cooperative multi task assignment problem of UAVs

In response to the increasing complexity of military operations, the use of multiple heterogeneous unmanned aerial vehicles (UAVs) is essential for efficiently executing complex missions. This paper introduces an extended cooperative multi-task assignment problem (ECMTAP), which involves deploying heterogeneous UAVs from different base stations to accomplish specific missions, with a focus on minimizing overall mission completion time. ECMTAP categorizes targets into various types, each associated with unique task sets including {reconnaissance}, {attack, evaluation}, and {reconnaissance, attack, evaluation}. ECMTAP requires that attack tasks follow reconnaissance tasks, and evaluation tasks follow attack tasks, adding complexity due to specific timing constraints on each task. To tackle this problem, we propose a novel algorithm, the reinforcement search strategy-based adaptive large neighborhood search (RSALNS). To enhance the search capability, RASLNS utilizes two key destroy-repair operations: the intra-target tasks adjustment strategy and the evaluation tasks adjustment strategy. The former operation dismantles and reconstructs task sequences within a target, potentially resulting in suboptimal assignment of evaluation tasks, while the latter operation reassigns these tasks based on the first operation's output. Extensive experiments validate the effectiveness of the RSALNS algorithm in solving the ECMTAP, demonstrating its capability to generate high-quality solutions efficiently.

Research on Enhancement of Gov't Functions in Regional Tech Achievements Transformation

The transformation of regional scientific and technological achievements is an important process of converting scientific research achievements into real productive forces, and the uneven distribution of regional resources is an inevitable problem in cross-regional innovation cooperation. To make up for the gap in scientific and technological resources, the cross-regional flow of technology has become an inevitable trend. While giving full play to the role of the market in resource allocation, it is even more necessary to give full play to the leading role of the government. With the introduction of a series of relevant laws and policies in China, the function of the government in the cross-regional transformation of scientific and technological achievements has been increasingly enhanced, but in this process, there are still deficiencies in the government's role positioning, relevant policies for interest balance, and the inter-governmental cooperation mechanism among regions. Based on this, it is necessary to optimize the function of the government in the transformation of regional scientific and technological achievements, effectively play the leading role of the government, construct an efficient and collaborative scientific and technological transformation mechanism, and cultivate the cooperation awareness of various participating subjects, so as to provide useful thinking for improving the function of the government in regional scientific and technological transformation.

Adaptive Distributed Heterogeneous Formation Control for UAV-USVs with Input Quantization

This paper investigates the cooperative formation trajectory tracking problem for heterogeneous unmanned aerial vehicle (UAV) and multiple unmanned surface vessel (USV) systems with input quantization performance. Firstly, at the kinematic level, a distributed guidance law based on an extended state observer (ESO) is designed to compensate for the unknown speed of neighbor agents for expected trajectory tracking, and subsequently at the dynamic level, an ESO is utilized to estimate model uncertainties and environmental disturbances. Following that, a linear analytic model is employed to depict the input quantization process, and the corresponding adaptive quantization controller is designed without necessitating prior information on quantization parameters. Based on the input-to-state stability, the stability of the proposed control structure is proved, and all the signals in the closed-loop system are ultimately bounded. Finally, a simulation study is provided to show the efficacy of the proposed strategy.

Math-LIGHT problem posing by three experts with different fields of expertise: Why? What? and How?

The Math-LIGHT program is directed at promoting literacy-rich mathematical instruction in middle school. A team of designers with different types of expertise pose Math-Light problems. We perform comparative analysis of problem-posing activities by experts with different types of expertise. We demonstrate that Activity Theory (Leontiev, 1978) is a powerful theoretical framework for the analysis of the structure of problem posing activity. Framed by activity theory we ask “Why?” questions to understand the main goals of posing problems; “What?” questions are directed at the characteristics of the PP process and PP products; and “How?” questions are aimed at identifying the tools used by the designers to fit the conditions in which the problems are implemented. We find that the three designers’ problem-posing activities are complimentary and suggest that the cooperative problem posing process is essential for posing problems that integrate different perspectives and thus allow more goals to be attained.

Арктическая повестка Петербургского международного экономического форума (ПМЭФ-2023)

The article summarizes the general results of the 26th St. Petersburg International Economic Forum (SPIEF-2023), which took place in St. Petersburg from 14 to 17 June 2023. The author, as a participant of the forum, attended all 15 events of the business program “The Arctic: Territory of Dialogue”, organized by the Ministry for the Development of the Far East and the Arctic. The article focuses on the problems of international cooperation, including with Asian countries, and the development of the Northern Sea Route.

Evolution game simulation study on Asia–Europe grain trade cooperation network

There has unavoidably been a problem for international grain cooperation in the Asia–Europe region as a result of the Russian–Ukrainian conflict. Analysis of the impact of Russian–Ukrainian conflict on the evolution of grain trade cooperation, identifying key influencing factors and formulating corresponding measures are of practical value for safeguarding grain security in the Asia–Europe region. In this paper, a grain trade network is constructed according to grain trade data from the Asian–European grain trade cooperation countries. A grain trade network game (GTNG) model of grain trade cooperation is established in order to investigate the elements that influence trade cooperation. The reciprocal preference is introduced. Through simulation experiments, the effects of cooperation costs, neighboring countries’ incentives, and punitive pressures, the degree of goodwill perception, the types of game, and the proportion of initial cooperators on trade cooperation are examined. This study may give useful policy recommendations for promoting Asia–Europe grain trade cooperation under the influence of the Russian–Ukrainian conflict.