6 papers · 1 filter
Combining Reinforcement Learning with Arc-search Interior-Point Method for Path Planning
Yaguang Yang, Qiang Le, Isaac E. Weintraub
Path planning in environments containing obstacles has numerous practical applications. The problem is challenging because it is inherently nonlinear and nonconvex. Consequently, a…
A Comparison of Reinforcement Learning and Optimal Control Methods for Path Planning
Qiang Le, Yaguang Yang, Isaac E. Weintraub
Path-planning for autonomous vehicles in threat-laden environments is a fundamental challenge. While traditional optimal control methods can find ideal paths, the computational tim…
Safe Navigation in the Presence of Range-Limited Pursuers
Thomas Chapman, Alexander Von Moll, Isaac E. Weintraub
This paper examines the degree to which an evader seeking a safe and efficient path to a target location can benefit from increasing levels of knowledge regarding one or more range…
Reactive Vehicle Guidance using Dynamic Maneuvering Cue
Alexander Von Moll, Isaac Weintraub
Recent approaches for navigating among dynamic threat regions (i.e., weapon engagement zones) have focused on planning entire trajectories. Moreover, the allowance for penetration…
One-vs-one Threat-Aware Weaponeering with Basic Engagement Zones
Alexander Von Moll, Dejan MilutinoviÄ, Isaac Weintraub +1
In this paper we address the problem of 'weaponeering', i.e., placing the weapon engagement zone (WEZ) of a vehicle on a moving target, while simultaneously avoiding the target's W…
Engagement Zones for a Turn Constrained Pursuer
Thomas Chapman, Isaac E. Weintraub, Alexander Von Moll +1
This work derives two basic engagement zone models, describing regions of potential risk or capture for a mobile vehicle by a pursuer. The pursuer is modeled as having turn-constra…