Zobrazeno 1 - 10
of 239
pro vyhledávání: '"Voulgaris, Petros"'
Autor:
Tao, Ran, Kim, Hunmin, Yoon, Hyung-Jin, Wan, Wenbin, Hovakimyan, Naira, Sha, Lui, Voulgaris, Petros
This article proposes and evaluates a new safety concept called backup plan safety for path planning of autonomous vehicles under mission uncertainty using model predictive control (MPC). Backup plan safety is defined as the ability to complete an al
Externí odkaz:
http://arxiv.org/abs/2306.06102
Fundamental limitations or performance trade-offs/limits are important properties and constraints of control and filtering systems. Among various trade-off metrics, total information rate, which characterizes the sensitivity trade-offs and average pe
Externí odkaz:
http://arxiv.org/abs/2304.09274
The deep neural network (DNN) models for object detection using camera images are widely adopted in autonomous vehicles. However, DNN models are shown to be susceptible to adversarial image perturbations. In the existing methods of generating the adv
Externí odkaz:
http://arxiv.org/abs/2212.13667
Autor:
Yoon, Hyung-Jin, Voulgaris, Petros
Due to recent climate changes, we have seen more frequent and severe wildfires in the United States. Predicting wildfires is critical for natural disaster prevention and mitigation. Advances in technologies in data processing and communication enable
Externí odkaz:
http://arxiv.org/abs/2209.10102
Heterogeneous networks comprise agents with varying capabilities in terms of computation, storage, and communication. In such settings, it is crucial to factor in the operating characteristics in allowing agents to choose appropriate updating schemes
Externí odkaz:
http://arxiv.org/abs/2209.01276
Safe control designs for robotic systems remain challenging because of the difficulties of explicitly solving optimal control with nonlinear dynamics perturbed by stochastic noise. However, recent technological advances in computing devices enable on
Externí odkaz:
http://arxiv.org/abs/2206.11985
This paper presents a family of algorithms for decentralized convex composite problems. We consider the setting of a network of agents that cooperatively minimize a global objective function composed of a sum of local functions plus a regularizer. Th
Externí odkaz:
http://arxiv.org/abs/2204.06380
The use of random sampling in decision-making and control has become popular with the ease of access to graphic processing units that can generate and calculate multiple random trajectories for real-time robotic applications. In contrast to sequentia
Externí odkaz:
http://arxiv.org/abs/2203.10067
We propose a communication efficient quasi-Newton method for large-scale multi-agent convex composite optimization. We assume the setting of a network of agents that cooperatively solve a global minimization problem with strongly convex local cost fu
Externí odkaz:
http://arxiv.org/abs/2201.03759
As wildfires are expected to become more frequent and severe, improved prediction models are vital to mitigating risk and allocating resources. With remote sensing data, valuable spatiotemporal statistical models can be created and used for resource
Externí odkaz:
http://arxiv.org/abs/2111.14038