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pro vyhledávání: '"Chee, Kong Yao"'
Flying quadrotors in tight formations is a challenging problem. It is known that in the near-field airflow of a quadrotor, the aerodynamic effects induced by the propellers are complex and difficult to characterize. Although machine learning tools ca
Externí odkaz:
http://arxiv.org/abs/2410.09727
With the increase in data availability, it has been widely demonstrated that neural networks (NN) can capture complex system dynamics precisely in a data-driven manner. However, the architectural complexity and nonlinearity of the NNs make it challen
Externí odkaz:
http://arxiv.org/abs/2308.08086
The recent increase in data availability and reliability has led to a surge in the development of learning-based model predictive control (MPC) frameworks for robot systems. Despite attaining substantial performance improvements over their non-learni
Externí odkaz:
http://arxiv.org/abs/2308.00570
Nonlinear model predictive control (MPC) is a flexible and increasingly popular framework used to synthesize feedback control strategies that can satisfy both state and control input constraints. In this framework, an optimization problem, subjected
Externí odkaz:
http://arxiv.org/abs/2211.13829
Autor:
Chee, Kong Yao, Hsieh, M. Ani
State estimation is an important aspect in many robotics applications. In this work, we consider the task of obtaining accurate state estimates for robotic systems by enhancing the dynamics model used in state estimation algorithms. Existing framewor
Externí odkaz:
http://arxiv.org/abs/2209.08185
In this work, we consider the task of improving the accuracy of dynamic models for model predictive control (MPC) in an online setting. Although prediction models can be learned and applied to model-based controllers, these models are often learned o
Externí odkaz:
http://arxiv.org/abs/2207.09344
In this work, we consider the problem of deriving and incorporating accurate dynamic models for model predictive control (MPC) with an application to quadrotor control. MPC relies on precise dynamic models to achieve the desired closed-loop performan
Externí odkaz:
http://arxiv.org/abs/2109.04821
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