Zobrazeno 1 - 10
of 15 649
pro vyhledávání: '"Burdick A"'
Since the COVID-19 pandemic, clinicians have seen a large and sustained influx in patient portal messages, significantly contributing to clinician burnout. To the best of our knowledge, there are no large-scale public patient portal messages corpora
Externí odkaz:
http://arxiv.org/abs/2411.06549
Autor:
Kurtz, Vince, Burdick, Joel W.
The recent success of diffusion-based generative models in image and natural language processing has ignited interest in diffusion-based trajectory optimization for nonlinear control systems. Existing methods cannot, however, handle the nonlinear equ
Externí odkaz:
http://arxiv.org/abs/2410.01939
This paper develops a Bayesian optimal experimental design for robot kinematic calibration on ${\mathbb{S}^3 \!\times\! \mathbb{R}^3}$. Our method builds upon a Gaussian process approach that incorporates a geometry-aware kernel based on Riemannian M
Externí odkaz:
http://arxiv.org/abs/2409.10802
Autor:
Kurtz, Vince, Burdick, Joel W.
Supervised machine learning is powerful. In recent years, it has enabled massive breakthroughs in computer vision and natural language processing. But leveraging these advances for optimal control has proved difficult. Data is a key limiting factor.
Externí odkaz:
http://arxiv.org/abs/2409.05792
This paper considers three related mobile robot multi-target sensory coverage and inspection planning problems in 2-D environments. In the first problem, a mobile robot must find the shortest path to observe multiple targets with a limited range sens
Externí odkaz:
http://arxiv.org/abs/2405.15100
Autor:
Akella, Prithvi, Dixit, Anushri, Ahmadi, Mohamadreza, Lindemann, Lars, Chapman, Margaret P., Pappas, George J., Ames, Aaron D., Burdick, Joel W.
The need for a systematic approach to risk assessment has increased in recent years due to the ubiquity of autonomous systems that alter our day-to-day experiences and their need for safety, e.g., for self-driving vehicles, mobile service robots, and
Externí odkaz:
http://arxiv.org/abs/2403.18972
This paper develops rollover prevention guarantees for mobile robots using control barrier function (CBF) theory, and demonstrates the method experimentally. We consider a safety measure based on a zero moment point condition through the lens of CBFs
Externí odkaz:
http://arxiv.org/abs/2403.08916
This work presents a novel data-driven multi-layered planning and control framework for the safe navigation of a class of unmanned ground vehicles (UGVs) in the presence of unknown stationary obstacles and additive modeling uncertainties. The foundat
Externí odkaz:
http://arxiv.org/abs/2403.03215
Autor:
Das, Ersin, Burdick, Joel W.
This paper proposes a safety-critical control design approach for nonlinear control affine systems in the presence of matched and unmatched uncertainties. Our constructive framework couples control barrier function (CBF) theory with a new uncertainty
Externí odkaz:
http://arxiv.org/abs/2401.01881
Autor:
Masoero, Lorenzo, Vijaykumar, Suhas, Richardson, Thomas, McQueen, James, Rosen, Ido, Burdick, Brian, Bajari, Pat, Imbens, Guido
Classical designs of randomized experiments, going back to Fisher and Neyman in the 1930s still dominate practice even in online experimentation. However, such designs are of limited value for answering standard questions in settings, common in marke
Externí odkaz:
http://arxiv.org/abs/2401.01264