منابع مشابه
Path planning under spatial uncertainty.
In this article, we present experiments studying path planning under spatial uncertainties. In the main experiment, the participants' task was to navigate the shortest possible path to find an object hidden in one of four places and to bring it to the final destination. The probability of finding the object (probability matrix) was different for each of the four places and varied between condit...
متن کاملRunning head: PATH PLANNING UNDER SPATIAL UNCERTAINTY
We present experiments studying path planning under spatial uncertainties. In the main experiment, participants’ task was to navigate the shortest possible path to find an object, hidden in one of 4 places, and to bring it to the final destination. The probability of finding the object was different for the 4 places (probability matrix) and varied between conditions. Given such uncertainties ab...
متن کاملPath Planning under Time-Dependent Uncertainty
Standard algorithms for finding the short est path in a graph require that the cost of a path be additive in edge costs, and typically assume that costs are determinis tic. We consider the problem of uncertain edge costs, with potential probabilistic de pendencies among the costs. Although these dependencies violate the standard dynamic programming decomposition, we identify a weaker stocha...
متن کاملPractical Route Planning Under Delay Uncertainty: Stochastic Shortest Path Queries
We describe an algorithm for stochastic path planning and applications to route planning in the presence of traffic delays. We improve on the prior state of the art by designing, analyzing, implementing, and evaluating data structures that answer approximate stochastic shortest-path queries. For example, our data structures can be used to efficiently compute paths that maximize the probability ...
متن کاملRobust Path Planning and Feedback Design under Stochastic Uncertainty
Autonomous vehicles require optimal path planning algorithms to achieve mission goals while avoiding obstacles and being robust to uncertainties. The uncertainties arise from exogenous disturbances, modeling errors, and sensor noise, which can be characterized via stochastic models. Previous work defined a notion of robustness in a stochastic setting by using the concept of chance constraints. ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Memory & Cognition
سال: 2008
ISSN: 0090-502X,1532-5946
DOI: 10.3758/mc.36.3.495