Zobrazeno 1 - 10
of 6 395
pro vyhledávání: '"A. Hoxha"'
The tendency of repeating past choices more often than expected from the history of outcomes has been repeatedly empirically observed in reinforcement learning experiments. It can be explained by at least two computational processes: asymmetric updat
Externí odkaz:
http://arxiv.org/abs/2410.19434
Autor:
Long, Kehan, Parwana, Hardik, Fainekos, Georgios, Hoxha, Bardh, Okamoto, Hideki, Atanasov, Nikolay
This paper presents a novel method for modeling the shape of a continuum robot as a Neural Configuration Euclidean Distance Function (N-CEDF). By learning separate distance fields for each link and combining them through the kinematics chain, the lea
Externí odkaz:
http://arxiv.org/abs/2409.13865
Autor:
Parwana, Hardik, Black, Mitchell, Fainekos, Georgios, Hoxha, Bardh, Okamoto, Hideki, Prokhorov, Danil
The rapid advancement of robotics necessitates robust tools for developing and testing safe control architectures in dynamic and uncertain environments. Ensuring safety and reliability in robotics, especially in safety-critical applications, is cruci
Externí odkaz:
http://arxiv.org/abs/2407.13693
Deep metric learning (DML) has shown to be effective for content-based image retrieval (CBIR) in remote sensing (RS). Most of DML methods for CBIR rely on a high number of annotated images to accurately learn model parameters of deep neural networks
Externí odkaz:
http://arxiv.org/abs/2406.10107
Autor:
Hoxha, Klajdi
How do consultants price expertise? This paper studies a problem of selling information products (expertise) to a buyer (client) who faces decision-making problem under uncertainty. The client is privately informed about the type of expertise she nee
Externí odkaz:
http://arxiv.org/abs/2405.11142
This paper introduces CBFKit, a Python/ROS toolbox for safe robotics planning and control under uncertainty. The toolbox provides a general framework for designing control barrier functions for mobility systems within both deterministic and stochasti
Externí odkaz:
http://arxiv.org/abs/2404.07158
This paper addresses the problem of risk-aware fixed-time stabilization of a class of uncertain, output-feedback nonlinear systems modeled via stochastic differential equations. First, novel classes of certificate functions, namely risk-aware fixed-t
Externí odkaz:
http://arxiv.org/abs/2403.20258
This paper introduces a model-based approach for training feedback controllers for an autonomous agent operating in a highly nonlinear (albeit deterministic) environment. We desire the trained policy to ensure that the agent satisfies specific task o
Externí odkaz:
http://arxiv.org/abs/2403.15826
Autor:
Tuck, Victoria Marie, Chen, Pei-Wei, Fainekos, Georgios, Hoxha, Bardh, Okamoto, Hideki, Sastry, S. Shankar, Seshia, Sanjit A.
Multi-Robot Task Allocation (MRTA) is a problem that arises in many application domains including package delivery, warehouse robotics, and healthcare. In this work, we consider the problem of MRTA for a dynamic stream of tasks with task deadlines an
Externí odkaz:
http://arxiv.org/abs/2403.11737
Autor:
Watanabe, Kandai, Fainekos, Georgios, Hoxha, Bardh, Lahijanian, Morteza, Okamoto, Hideki, Sankaranarayanan, Sriram
This paper addresses the challenge of planning a sequence of tasks to be performed by multiple robots while minimizing the overall completion time subject to timing and precedence constraints. Our approach uses the Timed Partial Orders (TPO) model to
Externí odkaz:
http://arxiv.org/abs/2405.00687