Based on the double integrator mathematic model, a new kind of potential function is presented in this paper by referring to the concepts of the electric field; then a new formation control method is proposed, in whic...Based on the double integrator mathematic model, a new kind of potential function is presented in this paper by referring to the concepts of the electric field; then a new formation control method is proposed, in which the potential functions are used between agent-agent and between agent-obstacle, while state feedback control is applied for the agent and its goal. This strategy makes the whole potential field simpler and helps avoid some local minima. The stability of this combination of potential functions and state feedback control is proven. Some simulations are presented to show the rationality of this control method.展开更多
In view of the complex marine environment of navigation,especially in the case of multiple static and dynamic obstacles,the traditional obstacle avoidance algorithms applied to unmanned surface vehicles(USV)are prone ...In view of the complex marine environment of navigation,especially in the case of multiple static and dynamic obstacles,the traditional obstacle avoidance algorithms applied to unmanned surface vehicles(USV)are prone to fall into the trap of local optimization.Therefore,this paper proposes an improved artificial potential field(APF)algorithm,which uses 5G communication technology to communicate between the USV and the control center.The algorithm introduces the USV discrimination mechanism to avoid the USV falling into local optimization when the USV encounter different obstacles in different scenarios.Considering the various scenarios between the USV and other dynamic obstacles such as vessels in the process of performing tasks,the algorithm introduces the concept of dynamic artificial potential field.For the multiple obstacles encountered in the process of USV sailing,based on the International Regulations for Preventing Collisions at Sea(COLREGS),the USV determines whether the next step will fall into local optimization through the discriminationmechanism.The local potential field of the USV will dynamically adjust,and the reverse virtual gravitational potential field will be added to prevent it from falling into the local optimization and avoid collisions.The objective function and cost function are designed at the same time,so that the USV can smoothly switch between the global path and the local obstacle avoidance.The simulation results show that the improved APF algorithm proposed in this paper can successfully avoid various obstacles in the complex marine environment,and take navigation time and economic cost into account.展开更多
By using the pseudo minimum translational distance between convexobjects, this paper presents two algorithms for robot path planning. First, an analytically tractable potential field is defined in the robot configurat...By using the pseudo minimum translational distance between convexobjects, this paper presents two algorithms for robot path planning. First, an analytically tractable potential field is defined in the robot configuration space, and the concept of virtual obstacles is introduced and incorporated in the path planner to handle the local minima of the potential function. Second, based on the Lipschitz continuity and differentiability of the pseudo minimum translational distance, the flexible-trajectory approach is implemented. Simulation examples are given to show the effectiveness and efficiency of the path planners for both mobile robots and manipulators.展开更多
In this paper, the fixed-time event-triggered obstacle avoidance consensus control for a multi-AUV time-varying formation system in a 3D environment is presented by using an improved artificial potential field and lea...In this paper, the fixed-time event-triggered obstacle avoidance consensus control for a multi-AUV time-varying formation system in a 3D environment is presented by using an improved artificial potential field and leader-follower strategy(IAPF-LF). Firstly, the proposed fixed-time control can achieve the desired multi-AUV formation within a fixed settling time in any initial system state. Secondly, an event-triggered communication strategy is developed to govern the communication among AUVs, and the communication energy consumption can be decremented. The time-varying formation obstacle avoidance control algorithm based on IAPF-LF is designed to avoid static and dynamic obstacles, the desired formation is maintained in the presence of external disturbances, and there is no Zeno behavior under the fixed-time event-triggered consensus control strategy.The stability of the system is proved by the Lyapunov function and inequality scaling. Finally, simulation examples and water pool experiments are reported to verify the performance of the proposed theoretical algorithms.展开更多
Inspired by the pigeon behavior pattern,this paper proposes an Unmanned Aerial Vehicle(UAV)swarm control scheme based on hybrid bionic sw arm intelligence,which can realize multi-UAV obstacle avoidance d uring formati...Inspired by the pigeon behavior pattern,this paper proposes an Unmanned Aerial Vehicle(UAV)swarm control scheme based on hybrid bionic sw arm intelligence,which can realize multi-UAV obstacle avoidance d uring formation control.First,the leadership mechanism of pigeon flock is mapped to UAV swamm,and the virtual leaders are introduced to solve the unfixed relative position of level-1 leader problem.Second,the control law for UAV swarm formation is designed based on artificial potential field theory and analysis of the bionic mechanism.To avoid local minima,a guidance phase is added to the UAV formation process.By analyzing the flocking algorithm,a cooperative interaction control model of UAV swarm is established.Third,the coopentive interactive control law for UAV sw arm obstacle avoidance is proposed based on improved artifcial potential feld function.Then the two bionic swarm control models are combined to realize the formation and obstacle avoidance of UAV swarm based on mixed bionic swarm intelligence.Finally,a series of simulations are conducted to demonstrate the proposed hybrid UAV sw arm control algorithm.展开更多
基金the Jiangsu Province Fundamental Research Plan (Natural Science Foundation) (No.BK2006202).
文摘Based on the double integrator mathematic model, a new kind of potential function is presented in this paper by referring to the concepts of the electric field; then a new formation control method is proposed, in which the potential functions are used between agent-agent and between agent-obstacle, while state feedback control is applied for the agent and its goal. This strategy makes the whole potential field simpler and helps avoid some local minima. The stability of this combination of potential functions and state feedback control is proven. Some simulations are presented to show the rationality of this control method.
基金This work was supported by the Postdoctoral Fund of FDCT,Macao(Grant No.0003/2021/APD).Any opinions,findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect those of the sponsor.
文摘In view of the complex marine environment of navigation,especially in the case of multiple static and dynamic obstacles,the traditional obstacle avoidance algorithms applied to unmanned surface vehicles(USV)are prone to fall into the trap of local optimization.Therefore,this paper proposes an improved artificial potential field(APF)algorithm,which uses 5G communication technology to communicate between the USV and the control center.The algorithm introduces the USV discrimination mechanism to avoid the USV falling into local optimization when the USV encounter different obstacles in different scenarios.Considering the various scenarios between the USV and other dynamic obstacles such as vessels in the process of performing tasks,the algorithm introduces the concept of dynamic artificial potential field.For the multiple obstacles encountered in the process of USV sailing,based on the International Regulations for Preventing Collisions at Sea(COLREGS),the USV determines whether the next step will fall into local optimization through the discriminationmechanism.The local potential field of the USV will dynamically adjust,and the reverse virtual gravitational potential field will be added to prevent it from falling into the local optimization and avoid collisions.The objective function and cost function are designed at the same time,so that the USV can smoothly switch between the global path and the local obstacle avoidance.The simulation results show that the improved APF algorithm proposed in this paper can successfully avoid various obstacles in the complex marine environment,and take navigation time and economic cost into account.
基金This work is supported by the National Natural Science Foundation of China (Grant Nos. 59805004, 59990470) National Distinguished Youth Foundation (59725514).
文摘By using the pseudo minimum translational distance between convexobjects, this paper presents two algorithms for robot path planning. First, an analytically tractable potential field is defined in the robot configuration space, and the concept of virtual obstacles is introduced and incorporated in the path planner to handle the local minima of the potential function. Second, based on the Lipschitz continuity and differentiability of the pseudo minimum translational distance, the flexible-trajectory approach is implemented. Simulation examples are given to show the effectiveness and efficiency of the path planners for both mobile robots and manipulators.
基金supported in part by the National Natural Science Foundation of China (62033009)the Creative Activity Plan for Science and Technology Commission of Shanghai (20510712300,21DZ2293500)the Supported by Science Foundation of Donghai Laboratory。
文摘In this paper, the fixed-time event-triggered obstacle avoidance consensus control for a multi-AUV time-varying formation system in a 3D environment is presented by using an improved artificial potential field and leader-follower strategy(IAPF-LF). Firstly, the proposed fixed-time control can achieve the desired multi-AUV formation within a fixed settling time in any initial system state. Secondly, an event-triggered communication strategy is developed to govern the communication among AUVs, and the communication energy consumption can be decremented. The time-varying formation obstacle avoidance control algorithm based on IAPF-LF is designed to avoid static and dynamic obstacles, the desired formation is maintained in the presence of external disturbances, and there is no Zeno behavior under the fixed-time event-triggered consensus control strategy.The stability of the system is proved by the Lyapunov function and inequality scaling. Finally, simulation examples and water pool experiments are reported to verify the performance of the proposed theoretical algorithms.
文摘Inspired by the pigeon behavior pattern,this paper proposes an Unmanned Aerial Vehicle(UAV)swarm control scheme based on hybrid bionic sw arm intelligence,which can realize multi-UAV obstacle avoidance d uring formation control.First,the leadership mechanism of pigeon flock is mapped to UAV swamm,and the virtual leaders are introduced to solve the unfixed relative position of level-1 leader problem.Second,the control law for UAV swarm formation is designed based on artificial potential field theory and analysis of the bionic mechanism.To avoid local minima,a guidance phase is added to the UAV formation process.By analyzing the flocking algorithm,a cooperative interaction control model of UAV swarm is established.Third,the coopentive interactive control law for UAV sw arm obstacle avoidance is proposed based on improved artifcial potential feld function.Then the two bionic swarm control models are combined to realize the formation and obstacle avoidance of UAV swarm based on mixed bionic swarm intelligence.Finally,a series of simulations are conducted to demonstrate the proposed hybrid UAV sw arm control algorithm.
