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pro vyhledávání: '"Sprague, Christopher Iliffe"'
Modeling complex systems that evolve toward equilibrium distributions is important in various physical applications, including molecular dynamics and robotic control. These systems often follow the stochastic gradient descent of an underlying energy
Externí odkaz:
http://arxiv.org/abs/2410.11433
In contexts where data samples represent a physically stable state, it is often assumed that the data points represent the local minima of an energy landscape. In control theory, it is well-known that energy can serve as an effective Lyapunov functio
Externí odkaz:
http://arxiv.org/abs/2402.05774
Behavior trees (BTs) are an optimally modular framework to assemble hierarchical hybrid control policies from a set of low-level control policies using a tree structure. Many robotic tasks are naturally decomposed into a hierarchy of control tasks, a
Externí odkaz:
http://arxiv.org/abs/2308.08994
Behavior trees represent a hierarchical and modular way of combining several low-level control policies into a high-level task-switching policy. Hybrid dynamical systems can also be seen in terms of task switching between different policies, and ther
Externí odkaz:
http://arxiv.org/abs/2109.01575
Publikováno v:
IEEE Robotics and Automation Letters ( Volume: 5 , Issue: 3 , July 2020 )
Registration methods for point clouds have become a key component of many SLAM systems on autonomous vehicles. However, an accurate estimate of the uncertainty of such registration is a key requirement to a consistent fusion of this kind of measureme
Externí odkaz:
http://arxiv.org/abs/2003.10931
Optimal state-feedback controllers, capable of changing between different objective functions, are advantageous to systems in which unexpected situations may arise. However, synthesising such controllers, even for a single objective, is a demanding p
Externí odkaz:
http://arxiv.org/abs/1902.10139
Autor:
Sprague, Christopher Iliffe, Özkahraman, Özer, Munafo, Andrea, Marlow, Rachel, Phillips, Alexander, Ögren, Petter
In this paper, we show how behaviour trees (BTs) can be used to design modular, versatile, and robust control architectures for mission-critical systems. In particular, we show this in the context of autonomous underwater vehicles (AUVs). Robustness,
Externí odkaz:
http://arxiv.org/abs/1811.00426
In this paper, we show how Behavior Trees that have performance guarantees, in terms of safety and goal convergence, can be extended with components that were designed using machine learning, without destroying those performance guarantees. Machine l
Externí odkaz:
http://arxiv.org/abs/1809.10283
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