An observation-driven method for coordinated standoff target tracking based on Model Predictive control(MPC)is proposed to improve observation of multiple Unmanned Aerial Vehicles(UAVs)while approaching or loitering o...
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An observation-driven method for coordinated standoff target tracking based on Model Predictive control(MPC)is proposed to improve observation of multiple Unmanned Aerial Vehicles(UAVs)while approaching or loitering over a *** acquiring a fusion estimate of the target state,each UAV locally measures the observation capability of the entire UAV system with the Fisher Information Matrix(FIM)determinant in the decentralized *** facilitate observation optimization,only the FIM determinant is adopted to derive the performance function and control constraints for coordinated standoff ***,a modified iterative scheme is introduced to improve the iterative efficiency,and a consistent circular direction control is established to maintain long-term observation performance when the UAV approaches its *** experiments with simulated and real trajectories validate that the proposed method can improve observation of the UAV system for target tracking and adaptively optimize UAV trajectories according to sensor performance and UAV-target geometry.
The article analyzes modern computing devices that perform multiplication operations. The main classes of multipliers built on the basis of both electronic and optical elements are considered. The main disadvantage of...
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Eye contact is one of the main human skills, and a prerequisite of verbal language. However, children with Autism Spectrum Disorder (ASD) often have an important deficit in this skill, compromising their entire cognit...
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This article presents developments by its authors: the IndustrialKit library package and the RCWorkspace application based on it. The library allows developers of third-party applications to use the functionality of p...
This article presents developments by its authors: the IndustrialKit library package and the RCWorkspace application based on it. The library allows developers of third-party applications to use the functionality of programming and modeling robotic technological complexes in their products. The object-oriented concept of the package provides opportunities for offline training of manipulation robots in a developed simulation environment, subsequent transfer and launch of programs on real robots, organization of feedback control and obtaining statistical data from industrial equipment - common models of robots and various equipment devices, which is achieved through a unified structure of program modules. The connection of external visual models of production system components - robots, tools and parts - is demonstrated. An example of performing the task of assembling parts with spline joints is also given.
In this paper, the neural-network-based filtering problem is investigated for multi-sensor systems with dynamic encoding mechanisms. The sensor nodes and the remote filter are connected through bandwidth-constrained c...
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Pickup vehicle scheduling in the steel logistics park is a critical issue in determining the outbound effciency of steel products. Steel products are distributed in the yards of the steel logistics park with mixed sto...
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Reinforcement Learning (RL) based methods have became popular for control and motion planning of robots, recently. Unlike sampling based motion planners, optimal policies computed by them provide feedback motion plans...
Reinforcement Learning (RL) based methods have became popular for control and motion planning of robots, recently. Unlike sampling based motion planners, optimal policies computed by them provide feedback motion plans which eliminates the need for re-computing (optimal) trajectories when a robot starts from a different initial configuration each time. In related studies, an optimal policy (actor) and the associated value function (critic) are usually calculated preforming training in a simulation environment. During training, RL allows learning by interactions with the environment in a physically realistic manner. However, in a simulation system, it is possible to make physically unimplementable moves. Thus, instead of RL, one can make use of Dynamic Programming approaches such as Value Iteration for computing optimal policies, which does not require an exploration component and known to have better convergence properties. In addition, dimension of a value function is smaller than that of a Q-fuction, thereby lessening the severity of the curse of dimensionality. Motivated by these facts, the aim of this paper is to employ Value Iteration algorithm for motion planning of robot manipulators and elaborate its effectiveness compared to a popular RL method, Q-learning.
In order to be flexible and handle complex scenarios, intelligent automation systems might benefit from automated planning techniques which rely on specifications and models describing their behavior. However, due to ...
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In the present paper, a new model describing neutron star dynamics is analysed. The system under consideration can be described as a modified vortex creep model. Two component model and the vortex creep model have bee...
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In the present paper, a new model describing neutron star dynamics is analysed. The system under consideration can be described as a modified vortex creep model. Two component model and the vortex creep model have been used successfully to describe post glitch relaxation phase. However, glitch behaviour is yet to be explained. There can be a possible stochastic mechanism that trigger glitches in neutron stars. To this aim, we propose a modification in the nonlinear vortex creep model. The significance of the modification is twofold, the dynamics of the system is able to generate intermittency, imitating the glitch behaviour of pulsars, and the system also show chaotic motion when the system parameters are set accordingly. The chaotic dynamics is verified by using nonlinear tools such as numerical phase portraits, Lyapunov exponents and bifurcation diagrams.
Leader-follower collective motion is a key multi-agent network application. However, conventional methods struggle with high dynamics or communication interferences and fail to maintain consistent motion. To address t...
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