Existing path planning and coordination control methods for multi-robot systems(MRS) typically rely on predefined rules and rudimentary algorithms. However, these methods often struggle to adapt flexibly to complex en...
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Existing path planning and coordination control methods for multi-robot systems(MRS) typically rely on predefined rules and rudimentary algorithms. However, these methods often struggle to adapt flexibly to complex environments and to adjust motion targets appropriately. To address this challenge, this study presents a large language model(LLM)-assisted framework. By integrating textual descriptions of complex motion constraints, robot information, and local environmental data as inputs, LLMs generate motion objectives and translate them into executable control commands for the robots, thereby achieving coordinated control and path planning. This framework facilitates the generation, maintenance, and reshaping of formations in MRSs during path planning, applicable to both obstacle-free and obstacle-avoidance environments. Simulation results demonstrate that LLM-based control strategies enhance the autonomy, adaptability, flexibility, and robustness of MRS by processing complex information, making intelligent decisions, adapting to environmental changes, and handling disturbances and uncertainties.
Moving target defense (MTD) is a promising approach to defend against load redistribution attacks on the internet-of-things (IoT)-based smart grid networks by probing the distorted state estimates with the distributed...
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This study addresses the problem of guaranteed cost fault-tolerant fuzzy control for multiline re-entrant manufacturing systems (RMSs) against stochastic disturbances and workstation faults. Initially, a nonlinear hyp...
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Anovel control architecture is proposed to handle actuator failures in hybrid unmanned aerial vehicles (UAV). After detection of the failure, we switch from the nominal control law to a nonlinear model predictive cont...
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This paper presents a comprehensive study on efficient storage strategies and anomaly detection techniques tailored for multi-source heterogeneous subway monitoring data. By leveraging advanced deep learning models, w...
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This paper aims to achieve single-channel target speech extraction (TSE) in enclosures by solely utilizing distance information. This is the first work that utilizes only distance cues without using speaker physiologi...
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Trajectory tracking is a critical issue in the field of mobile robotics. This paper aims to design and implement a backstepping PID controller for trajectory tracking of a differential drive-wheeled mobile robot, eval...
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This paper discusses the design of a flight control system for an airplane whose aerodynamic elevators are damaged. An optimal control utilizing a Q-learning algorithm is designed to achieve the appropriate behavior o...
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Multi-object tracking (MOT) is one of the most important problems in computer vision and a key component of any vision-based perception system used in advanced autonomous mobile robotics. Therefore, its implementation...
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An Active Noise control (ANC) system based on a modified architecture is considered. This architecture allows to accelerate the convergence of the adaptive filtering algorithms in use. Besides, it allows to use the mo...
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