Off-road autonomous navigation is one of the most difficult automation challenges from the point of view of constraints on mobility, speed of motion, lack of environmental structur...
Reinforcement learning in real-world domains suffers from three curses of dimensionality: explosions in state and action spaces, and high stochasticity. We present approaches that ...
This paper studies the problem of real time yard crane dispatching in container terminals. Many technologies, including transponders, RFID and GPS have been used in the container ...
Xi Guo, Shell-Ying Huang, Wen-Jing Hsu, Malcolm Yo...
AUSNet is a functional network of autonomous undersea vehicles. We present two novel algorithms to enhance AUSNet. In live inwater testing, a packet queueing problem in which stal...
Matthew M. Haag, Emmanuel Agu, Rick Komerska, Stev...
We study the challenging problem of maneuvering object tracking with unknown dynamics, i.e., forces or torque. We investigate the underlying causes of object kinematics, and propo...