1 citations · 2 across the 28 of their papers we have counts for
6 papers · 1 filter
Risk-Aware Input-Constrained Safe Intercept Guidance Against Multiple Moving Defenders
Praveen Kumar Ranjan, Abhinav Sinha, Yongcan Cao +2
This paper develops a risk-aware guidance law for an attacker to intercept a stationary target in the presence of multiple moving defenders while respecting the control input limit…
Interception-Driven Inverse Reachability for Engagement Zone Construction
Grant Stagg, Cameron K. Peterson, Alexander Von Moll +1
In contested environments, autonomous vehicles may need to plan around adversarial pursuers whose launch locations are unknown. This paper presents an interception-driven inverse-r…
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…
Path Planning Using Deep Deterministic Policy Gradient: A Reinforcement Learning Approach
Qiang Le, Yaguang Yang, Isaac E. Weintraub
Path-planning for autonomous vehicles in threat-laden environments is a fundamental challenge because the problem is nonlinear and nonconvex even in simplest scenarios. While tradi…
Collaborative Threat-Aware Autonomy (CTAA)
Rajnikant Sharma, Abhinav Sinha, Isaac Weintraub
Navigating teams of unmanned vehicles through environments containing dynamic, adversarial Weapon Engagement Zones~(WEZs) poses a fundamental challenge to mission success: a single…
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…