Zobrazeno 1 - 10
of 364
pro vyhledávání: '"Mark, Nicholas"'
Autor:
Atanassov, Vassil, Yu, Wanming, Mitchell, Alexander Luis, Finean, Mark Nicholas, Havoutis, Ioannis
Representation learning and unsupervised skill discovery can allow robots to acquire diverse and reusable behaviors without the need for task-specific rewards. In this work, we use unsupervised reinforcement learning to learn a latent representation
Externí odkaz:
http://arxiv.org/abs/2410.07877
Despite the advantage quantum computers are expected to deliver when performing simulations compared to their classical counterparts, the current noisy intermediate-scale quantum (NISQ) devices remain limited in their capabilities. The training of pa
Externí odkaz:
http://arxiv.org/abs/2402.12105
The ability to shape health behaviors of large populations automatically, across wearable types and disease conditions at scale has tremendous potential to improve global health outcomes. We designed and implemented an AI driven platform for digital
Externí odkaz:
http://arxiv.org/abs/2401.10816
Autor:
Kristjuhan, Kaur, Jones, Mark Nicholas
We present a novel method for improving the quantum simulation of the ground state energy of molecules. We perform a pre-processing step classically, which reduces the dimensionality of the problem by generating a custom mapping which excludes states
Externí odkaz:
http://arxiv.org/abs/2303.01122
Publikováno v:
Communications Earth & Environment, Vol 5, Iss 1, Pp 1-11 (2024)
Abstract Waves are omnipresent in avalanches on Earth and other planets. The dynamic nature of waves makes them dangerous in geological hazards such as debris flows, turbidity currents, lava flows, and snow avalanches. Extensive research on granular
Externí odkaz:
https://doaj.org/article/3679a3351fbc4cc9a260065038dce6b0
Over the years, the separate fields of motion planning, mapping, and human trajectory prediction have advanced considerably. However, the literature is still sparse in providing practical frameworks that enable mobile manipulators to perform whole-bo
Externí odkaz:
http://arxiv.org/abs/2201.05058
Autor:
Nourbakhsh, Amirhossein, Jones, Mark Nicholas, Kristjuhan, Kaur, Carberry, Deborah, Karon, Jay, Beenfeldt, Christian, Shahriari, Kyarash, Andersson, Martin P., Jadidi, Mojgan A., Mansouri, Seyed Soheil
We use the benefits and components of classical computers every day. However, there are many types of problems which, as they grow in size, their computational complexity grows larger than classical computers will ever be able to solve. Quantum compu
Externí odkaz:
http://arxiv.org/abs/2201.02823
Publikováno v:
IEEE Robotics and Automation Letters, vol. 7, no. 2, pp. 1095-1102, April 2022
As robots operate in increasingly complex and dynamic environments, fast motion re-planning has become a widely explored area of research. In a real-world deployment, we often lack the ability to fully observe the environment at all times, giving ris
Externí odkaz:
http://arxiv.org/abs/2109.04721
Publikováno v:
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021, pp. 3710-3717
Recent work has demonstrated real-time mapping and reconstruction from dense perception, while motion planning based on distance fields has been shown to achieve fast, collision-free motion synthesis with good convergence properties. However, demonst
Externí odkaz:
http://arxiv.org/abs/2103.03958