Competition-based-winners-take-all(WTA)networks play a crucial role in multi-agent systems.However,existing WTA networks either neglect the impact of noise or only consider simple forms,such as constant noise.In pract...Competition-based-winners-take-all(WTA)networks play a crucial role in multi-agent systems.However,existing WTA networks either neglect the impact of noise or only consider simple forms,such as constant noise.In practice,noises often exhibit time-varying and nonlinear characteristics,which can be modeled using nonlinear functions and approximated by high-order polynomials.Such noises pose significant challenges for current WTA networks,limiting their practical applications.To address this,a WTA network with noise characteristics captured(WTA-NCC)is proposed in this article.Theoretical analyses demonstrate that the residual error of the proposed WTANCC network converges to zero globally,while simulation results confirm its robustness against polynomial noises.Additionally,a WTA coordination model is constructed by integrating the proposed network with a consensus estimator to achieve multi-agent tracking tasks.Finally,simulations and physical experiments are conducted further to demonstrate the validity and practicality of the WTA coordination model.展开更多
Aiming at the k-winners-take-all(kWTA)operation,this paper proposes a gradient-based differential kWTA(GDk WTA)network.After obtaining the network,theorems and related proofs are provided to guarantee the exponential ...Aiming at the k-winners-take-all(kWTA)operation,this paper proposes a gradient-based differential kWTA(GDk WTA)network.After obtaining the network,theorems and related proofs are provided to guarantee the exponential convergence and noise resistance of the proposed GD-kWTA network.Then,numerical simulations are conducted to substantiate the preferable performance of the proposed network as compared with the traditional ones.Finally,the GD-k WTA network,backed with a consensus filter,is utilized as a robust control scheme for modeling the competition behavior in the multi-robot coordination,thereby further demonstrating its effectiveness and feasibility.展开更多
This paper presents an adaptive formation control method for a heterogeneous robot swarm,utilising a multilevel formation task tree to model various types of formation tasks and a single-state distributed k-winner-tak...This paper presents an adaptive formation control method for a heterogeneous robot swarm,utilising a multilevel formation task tree to model various types of formation tasks and a single-state distributed k-winner-take-all(S-DKWTA)algorithm to address the MRTA problem.In addition,we propose an enhanced load reassignment algorithm to resolve conflicts when using S-DKWTA.The S-DKWTA algorithm demonstrates the capability to manage multiple objectives and dynamically select leaders in real-time,thereby optimising formation efficiency and reducing energy consumption.The proposed approach integrates an enhanced artificial potential field(APF)to govern the motion of heterogeneous robot systems which encompasses both unmanned ground vehicles(UGVs)and unmanned aerial vehicles(UAVs),thereby achieving collision and obstacle avoidance.Simulations employing UGVs and UAVs swarm to achieve formation movement demonstrate the efficacy of this approach.The amalgamation of S-DKWTA and improved APF ensures stable and adaptable formation control,underscoring its potential for diverse multirobot applications.展开更多
基金supported in part by the National Natural Science Foundation of China(62176109,62476115)in part by the Fundamental Research Funds for the Central Universities(lzuibky-2023-ey07)+1 种基金in part by the Youth and Middle-aged Scientific Research Foundation of Qinghai Normal University(2020QZR012)in part by the Supercomputing Center of Lanzhou University.
文摘Competition-based-winners-take-all(WTA)networks play a crucial role in multi-agent systems.However,existing WTA networks either neglect the impact of noise or only consider simple forms,such as constant noise.In practice,noises often exhibit time-varying and nonlinear characteristics,which can be modeled using nonlinear functions and approximated by high-order polynomials.Such noises pose significant challenges for current WTA networks,limiting their practical applications.To address this,a WTA network with noise characteristics captured(WTA-NCC)is proposed in this article.Theoretical analyses demonstrate that the residual error of the proposed WTANCC network converges to zero globally,while simulation results confirm its robustness against polynomial noises.Additionally,a WTA coordination model is constructed by integrating the proposed network with a consensus estimator to achieve multi-agent tracking tasks.Finally,simulations and physical experiments are conducted further to demonstrate the validity and practicality of the WTA coordination model.
基金supported in part by the National Natural Science Foundation of China(62176109)the Natural Science Foundation of Gansu Province(21JR7RA531)+6 种基金the Tibetan Information Processing and Machine Translation Key Laboratory of Qinghai Province(2021-Z-003)the CAS“Light of West China”Programthe Natural Science Foundation of Chongqing(China)(cstc2020jcyjzdxm X0028)the Chongqing Entrepreneurship and Innovation Support Program for Overseas Returnees(CX2021100)the Supercomputing Center of Lanzhou Universitythe Science and Technology Project of Chengguan District of Lanzhou(2021JSCX0014)the Education Department of Gansu Province:Excellent Graduate Student“Innovation Star”Project(2021CXZX-122)。
文摘Aiming at the k-winners-take-all(kWTA)operation,this paper proposes a gradient-based differential kWTA(GDk WTA)network.After obtaining the network,theorems and related proofs are provided to guarantee the exponential convergence and noise resistance of the proposed GD-kWTA network.Then,numerical simulations are conducted to substantiate the preferable performance of the proposed network as compared with the traditional ones.Finally,the GD-k WTA network,backed with a consensus filter,is utilized as a robust control scheme for modeling the competition behavior in the multi-robot coordination,thereby further demonstrating its effectiveness and feasibility.
基金supported by the National Natural Science Foundation of China(624B2140).
文摘This paper presents an adaptive formation control method for a heterogeneous robot swarm,utilising a multilevel formation task tree to model various types of formation tasks and a single-state distributed k-winner-take-all(S-DKWTA)algorithm to address the MRTA problem.In addition,we propose an enhanced load reassignment algorithm to resolve conflicts when using S-DKWTA.The S-DKWTA algorithm demonstrates the capability to manage multiple objectives and dynamically select leaders in real-time,thereby optimising formation efficiency and reducing energy consumption.The proposed approach integrates an enhanced artificial potential field(APF)to govern the motion of heterogeneous robot systems which encompasses both unmanned ground vehicles(UGVs)and unmanned aerial vehicles(UAVs),thereby achieving collision and obstacle avoidance.Simulations employing UGVs and UAVs swarm to achieve formation movement demonstrate the efficacy of this approach.The amalgamation of S-DKWTA and improved APF ensures stable and adaptable formation control,underscoring its potential for diverse multirobot applications.
