This paper introduces the Generalized Action Governor, which is a superv...
The action governor is an add-on scheme to a nominal control loop that
m...
Merging is, in general, a challenging task for both human drivers and
au...
Autonomous driving technologies are expected to not only improve mobilit...
In this paper, we introduce a set-theoretic approach for mobile robot
lo...
Quadcopters are increasingly used for applications ranging from hobby to...
This paper studies the problem of affine transformation-based guidance o...
Reinforcement Learning (RL) is essentially a trial-and-error learning
pr...
This paper proposes a learning reference governor (LRG) approach to enfo...
We propose a game theoretic approach to address the problem of searching...
It is not surprising that the idea of efficient maintenance algorithms
(...
With the number of small Unmanned Aircraft Systems (sUAS) in the nationa...
In this paper, we present a safe deep reinforcement learning system for
...
For a foreseeable future, autonomous vehicles (AVs) will operate in traf...
It is a long-standing goal of artificial intelligence (AI) to be superio...
n this paper, we describe an integrated framework for autonomous decisio...
In this paper, we describe a framework for autonomous decision making in...
Motivated by the need to develop simulation tools for verification and
v...
In this paper, we propose a decision making algorithm for autonomous veh...
As the connectivity of consumer devices is rapidly growing and cloud
com...