Zobrazeno 1 - 10
of 21 088
pro vyhledávání: '"Hawes BE"'
Disc galaxies represent a promising laboratory for the study of gravitational physics, including alternatives to dark matter, owing to the possibility of coupling rotation curves' dynamical data with strong gravitational lensing observations. In part
Externí odkaz:
http://arxiv.org/abs/2411.17888
Autor:
Rutherford, Alexander, Beukman, Michael, Willi, Timon, Lacerda, Bruno, Hawes, Nick, Foerster, Jakob
What data or environments to use for training to improve downstream performance is a longstanding and very topical question in reinforcement learning. In particular, Unsupervised Environment Design (UED) methods have gained recent attention as their
Externí odkaz:
http://arxiv.org/abs/2408.15099
Transparency in automated systems could be afforded through the provision of intelligible explanations. While transparency is desirable, might it lead to catastrophic outcomes (such as anxiety), that could outweigh its benefits? It's quite unclear ho
Externí odkaz:
http://arxiv.org/abs/2408.08785
We bring the Kerr--Newman spacetime into the Bondi--Sachs gauge by means of zero angular momentum, null geodesics. We compute the memory effect produced at the black hole horizon by a transient gravitational shock wave, which from future null infinit
Externí odkaz:
http://arxiv.org/abs/2407.15289
Autor:
Staniaszek, Michal, Flatscher, Tobit, Rowell, Joseph, Niu, Hanlin, Liu, Wenxing, You, Yang, Skilton, Robert, Fallon, Maurice, Hawes, Nick
We give an overview of AutoInspect, a ROS-based software system for robust and extensible mission-level autonomy. Over the past three years AutoInspect has been deployed in a variety of environments, including at a mine, a chemical plant, a mock oil
Externí odkaz:
http://arxiv.org/abs/2404.12785
Autor:
Gadd, Matthew, De Martini, Daniele, Pitt, Luke, Tubby, Wayne, Towlson, Matthew, Prahacs, Chris, Bartlett, Oliver, Jackson, John, Qi, Man, Newman, Paul, Hector, Andrew, Salguero-Gómez, Roberto, Hawes, Nick
We describe a challenging robotics deployment in a complex ecosystem to monitor a rich plant community. The study site is dominated by dynamic grassland vegetation and is thus visually ambiguous and liable to drastic appearance change over the course
Externí odkaz:
http://arxiv.org/abs/2404.10446
Publikováno v:
Advances in Neural Information Processing Systems 36 (2024)
Monte-Carlo Tree Search (MCTS) methods, such as Upper Confidence Bound applied to Trees (UCT), are instrumental to automated planning techniques. However, UCT can be slow to explore an optimal action when it initially appears inferior to other action
Externí odkaz:
http://arxiv.org/abs/2404.07732
Non-prehensile manipulation such as pushing is typically subject to uncertain, non-smooth dynamics. However, modeling the uncertainty of the dynamics typically results in intractable belief dynamics, making data-efficient planning under uncertainty d
Externí odkaz:
http://arxiv.org/abs/2404.02795
Publikováno v:
Mon.Not.Roy.Astron.Soc. 534 (2024) 3364-3376
Strong gravitational lens system catalogues are typically used to constrain a combination of cosmological and empirical power-law lens mass model parameters, often introducing additional empirical parameters and constraints from high resolution image
Externí odkaz:
http://arxiv.org/abs/2403.11997
Autor:
Brudermüller, Lara, Berger, Guillaume, Jankowski, Julius, Bhattacharyya, Raunak, Jungers, Raphaël, Hawes, Nick
Safety in the face of uncertainty is a key challenge in robotics. We introduce a real-time capable framework to generate safe and task-efficient robot motions for stochastic control problems. We frame this as a chance-constrained optimisation problem
Externí odkaz:
http://arxiv.org/abs/2402.01370