In complex water environments,search tasks often involve multiple Autonomous Underwater Vehicles(AUVs),and a single centralized control cannot handle the complexity and computational burden of large-scale systems.Targ...In complex water environments,search tasks often involve multiple Autonomous Underwater Vehicles(AUVs),and a single centralized control cannot handle the complexity and computational burden of large-scale systems.Target search in complex water environments has always been a major challenge in the field of underwater robots.To address this problem,this paper proposes a multi-biomimetic robot fish collaborative target search method based on Distributed Model Predictive Control(DMPC).First,we established a bionic robot fish kinematic model and a multi-biomimetic robot fish communication model;second,this paper proposed a distributed model predictive control algorithm based on the distributed search theory framework,so that the bionic robot fish can dynamically adjust their search path according to each other’s position information and search status,avoid repeated coverage or missing areas,and thus improve the search efficiency;third,we conducted simulation experiments based on DMPC,and the results showed that the proposed method has a target search success rate of more than 90%in static targets,dynamic targets,and obstacle environments.Finally,we compared this method with Centralized Model Predictive Control(CMPC)and Random Walk(RW)algorithms.The DMPC approach demonstrates significant advantages,achieving a remarkable target search success rate of 94.17%.These findings comprehensively validate the effectiveness and superiority of the proposed methodology.It can be seen that DMPC can effectively dispatch multiple bionic robot fish to work together to achieve efficient search of vast waters.It can significantly improve the flexibility,scalability,robustness and cooperation efficiency of the system and has broad application prospects.展开更多
With the increasing impacts of overfishing and environmental pollution,the deep-sea cage culture of marine fishes has become an important direction of mariculture.In this paper,a tuna-like robotic fish with a three-di...With the increasing impacts of overfishing and environmental pollution,the deep-sea cage culture of marine fishes has become an important direction of mariculture.In this paper,a tuna-like robotic fish with a three-dimensional helix path-following control system is designed for deep-sea net cage inspection.To mimic the flexibility of the fish’s movement,the kinematic model of the robotic fish adopts a tuna-like double-joint design with an addi-tional thruster device at the tail.Since the descending interval control plays a critical role in deep-sea net cage inspection,the control system utilizes the proportion integration differ-entiation(PID)based fuzzy logic control method to control the descending interval and yaw angle during the helix path movement.A polar coordinate path definition method is also proposed to simplify the reference path definition during net cage inspection.The experi-mental results demonstrates that the proposed three-dimensional path-following model can conduct net inspection task in an interferential environment and move along prede-fined reference path.展开更多
Fishes have learned how to achieve outstanding swimming performance through the evolution of hundreds of millions of years,which can provide bio-inspiration for robotic fish design.The premise of designing an excellen...Fishes have learned how to achieve outstanding swimming performance through the evolution of hundreds of millions of years,which can provide bio-inspiration for robotic fish design.The premise of designing an excellent robotic fish include fully understanding of fish locomotion mechanism and grasp of the advanced control strategy in robot domain.In this paper,the research development on fish swimming is presented,aiming to offer a reference for the later research.First,the research methods including experimental methods and simulation methods are detailed.Then the current research directions including fish locomotion mechanism,structure and function research and bionic robotic fish are outlined.Fish locomotion mechanism is discussed from three views:macroscopic view to find a unified principle,microscopic view to include muscle activity and intermediate view to study the behaviors of single fish and fish school.Structure and function research is mainly concentrated from three aspects:fin research,lateral line system and body stiffness.Bionic robotic fish research focuses on actuation,materials and motion control.The paper concludes with the future trend that curvature control,machine learning and multiple robotic fish system will play a more important role in this field.Overall,the intensive and comprehensive research on fish swimming will decrease the gap between robotic fish and real fish and contribute to the broad application prospect of robotic fish.展开更多
基金funded by National Natural Science Foundation of China(Nos.62473236,62073196).
文摘In complex water environments,search tasks often involve multiple Autonomous Underwater Vehicles(AUVs),and a single centralized control cannot handle the complexity and computational burden of large-scale systems.Target search in complex water environments has always been a major challenge in the field of underwater robots.To address this problem,this paper proposes a multi-biomimetic robot fish collaborative target search method based on Distributed Model Predictive Control(DMPC).First,we established a bionic robot fish kinematic model and a multi-biomimetic robot fish communication model;second,this paper proposed a distributed model predictive control algorithm based on the distributed search theory framework,so that the bionic robot fish can dynamically adjust their search path according to each other’s position information and search status,avoid repeated coverage or missing areas,and thus improve the search efficiency;third,we conducted simulation experiments based on DMPC,and the results showed that the proposed method has a target search success rate of more than 90%in static targets,dynamic targets,and obstacle environments.Finally,we compared this method with Centralized Model Predictive Control(CMPC)and Random Walk(RW)algorithms.The DMPC approach demonstrates significant advantages,achieving a remarkable target search success rate of 94.17%.These findings comprehensively validate the effectiveness and superiority of the proposed methodology.It can be seen that DMPC can effectively dispatch multiple bionic robot fish to work together to achieve efficient search of vast waters.It can significantly improve the flexibility,scalability,robustness and cooperation efficiency of the system and has broad application prospects.
基金This work is supported by the National Key Research and Development Program of China(Grant No.2019YFD0901000)the Key Technical Cooperation of Coastal Deep-water Probe(Grant No.2015DFA00090).
文摘With the increasing impacts of overfishing and environmental pollution,the deep-sea cage culture of marine fishes has become an important direction of mariculture.In this paper,a tuna-like robotic fish with a three-dimensional helix path-following control system is designed for deep-sea net cage inspection.To mimic the flexibility of the fish’s movement,the kinematic model of the robotic fish adopts a tuna-like double-joint design with an addi-tional thruster device at the tail.Since the descending interval control plays a critical role in deep-sea net cage inspection,the control system utilizes the proportion integration differ-entiation(PID)based fuzzy logic control method to control the descending interval and yaw angle during the helix path movement.A polar coordinate path definition method is also proposed to simplify the reference path definition during net cage inspection.The experi-mental results demonstrates that the proposed three-dimensional path-following model can conduct net inspection task in an interferential environment and move along prede-fined reference path.
基金National Natural Science Foundation of China(Grant No.51275127).
文摘Fishes have learned how to achieve outstanding swimming performance through the evolution of hundreds of millions of years,which can provide bio-inspiration for robotic fish design.The premise of designing an excellent robotic fish include fully understanding of fish locomotion mechanism and grasp of the advanced control strategy in robot domain.In this paper,the research development on fish swimming is presented,aiming to offer a reference for the later research.First,the research methods including experimental methods and simulation methods are detailed.Then the current research directions including fish locomotion mechanism,structure and function research and bionic robotic fish are outlined.Fish locomotion mechanism is discussed from three views:macroscopic view to find a unified principle,microscopic view to include muscle activity and intermediate view to study the behaviors of single fish and fish school.Structure and function research is mainly concentrated from three aspects:fin research,lateral line system and body stiffness.Bionic robotic fish research focuses on actuation,materials and motion control.The paper concludes with the future trend that curvature control,machine learning and multiple robotic fish system will play a more important role in this field.Overall,the intensive and comprehensive research on fish swimming will decrease the gap between robotic fish and real fish and contribute to the broad application prospect of robotic fish.
