Zobrazeno 1 - 10
of 57
pro vyhledávání: '"Duggirala, Parasara"'
Robotic perception models, such as Deep Neural Networks (DNNs), are becoming more computationally intensive and there are several models being trained with accuracy and latency trade-offs. However, modern latency accuracy trade-offs largely report me
Externí odkaz:
http://arxiv.org/abs/2207.06390
We propose a new technique for performing state space exploration of closed loop control systems with neural network feedback controllers. Our approach involves approximating the sensitivity of the trajectories of the closed loop dynamics. Using such
Externí odkaz:
http://arxiv.org/abs/2207.03884
In this work, we perform safety analysis of linear dynamical systems with uncertainties. Instead of computing a conservative overapproximation of the reachable set, our approach involves computing a statistical approximate reachable set. As a result,
Externí odkaz:
http://arxiv.org/abs/2109.07638
In this paper, we study the robustness of safety properties of a linear dynamical system with respect to model uncertainties. Our paper involves three parts. In the first part, we provide symbolic (analytical) and numerical (representation based) tec
Externí odkaz:
http://arxiv.org/abs/2109.07632
A robot can invoke heterogeneous computation resources such as CPUs, cloud GPU servers, or even human computation for achieving a high-level goal. The problem of invoking an appropriate computation model so that it will successfully complete a task w
Externí odkaz:
http://arxiv.org/abs/2108.01235
In this paper, we perform safety and performance analysis of an autonomous vehicle that implements reactive planner and controller for navigating a race lap. Unlike traditional planning algorithms that have access to a map of the environment, reactiv
Externí odkaz:
http://arxiv.org/abs/2107.05815
Reachable set computation is an important technique for the verification of safety properties of dynamical systems. In this paper, we investigate reachable set computation for discrete nonlinear systems based on parallelotope bundles. The algorithm r
Externí odkaz:
http://arxiv.org/abs/2105.11796
Autor:
Bak, Stanley, Bogomolov, Sergiy, Duggirala, Parasara Sridhar, Gerlach, Adam R., Potomkin, Kostiantyn
Reachability analysis of nonlinear dynamical systems is a challenging and computationally expensive task. Computing the reachable states for linear systems, in contrast, can often be done efficiently in high dimensions. In this paper, we explore veri
Externí odkaz:
http://arxiv.org/abs/2105.00886
In this paper, we propose a framework for performing state space exploration of closed loop control systems. Our approach involves approximating sensitivity and a newly introduced notion of inverse sensitivity by a neural network. We show how the app
Externí odkaz:
http://arxiv.org/abs/2007.05685
Publikováno v:
In Automatica July 2020 117
