问题描述：
英语翻译
Abstract
We propose real-time path planning schemes employing limited information for fully autonomous unmanned air vehicles (UAVs) in a hostile
environment.Two main algorithms are proposed under different assumptions on the information used and the threats involved.They consist of
several simple (computationally tractable) deterministic rules for real-time applications.The first algorithm uses extremely limited information
(only the probabilistic risk in the surrounding area with respect to the UAV’s current position) and memory,and the second utilizes more
knowledge (the location and strength of threats within the UAV’s sensory range) and memory.Both algorithms provably converge to a given
target point and produce a series of safe waypoints whose risk is almost less than a given threshold value.In particular,we characterize a
class of dynamic threats (so-called,static-dependent threats) so that the second algorithm can efficiently handle such dynamic threats while
guaranteeing its convergence to a given target.Challenging scenarios are used to test the proposed algorithms.
\3 2007 Elsevier Ltd.All rights reserved.
Keywords:Autonomous vehicles; Path planning; Limited data; Uncertainty; Static and dynamic threats
我的分不多 翻译的号再加分吧··
Abstract
We propose real-time path planning schemes employing limited information for fully autonomous unmanned air vehicles (UAVs) in a hostile
environment.Two main algorithms are proposed under different assumptions on the information used and the threats involved.They consist of
several simple (computationally tractable) deterministic rules for real-time applications.The first algorithm uses extremely limited information
(only the probabilistic risk in the surrounding area with respect to the UAV’s current position) and memory,and the second utilizes more
knowledge (the location and strength of threats within the UAV’s sensory range) and memory.Both algorithms provably converge to a given
target point and produce a series of safe waypoints whose risk is almost less than a given threshold value.In particular,we characterize a
class of dynamic threats (so-called,static-dependent threats) so that the second algorithm can efficiently handle such dynamic threats while
guaranteeing its convergence to a given target.Challenging scenarios are used to test the proposed algorithms.
\3 2007 Elsevier Ltd.All rights reserved.
Keywords:Autonomous vehicles; Path planning; Limited data; Uncertainty; Static and dynamic threats
我的分不多 翻译的号再加分吧··
问题解答：
我来补答展开全文阅读