Autonomous underwater vehicle plays a more and more important role in the exploration of
marine resources. Path planning and obstacle avoidance is the core technology to realize …

Reinforcement Learning is an area of Machine Learning focused on how agents can be
trained to make sequential decisions, and achieve a particular goal within an arbitrary …

Offline reinforcement learning (RL) defines the task of learning from a fixed batch of data.
Due to errors in value estimation from out-of-distribution actions, most offline RL algorithms …

Reinforcement learning from expert demonstrations (RLED) is the intersection of imitation
learning with reinforcement learning that seeks to take advantage of these two learning …

Evacuation planning and emergency routing systems are crucial in saving lives during
disasters. Traditional emergency routing systems, despite their best efforts, often struggle to …

While current autonomous navigation systems allow robots to successfully drive themselves
from one point to another in specific environments, they typically require extensive manual …

Surgical robot automation has attracted increasing research interest over the past decade,
expecting its potential to benefit surgeons, nurses and patients. Recently, the learning …

Task automation of surgical robot has the potentials to improve surgical efficiency. Recent
reinforcement learning (RL) based approaches provide scalable solutions to surgical …

This paper focuses on obstacle avoidance for the environmentally-driven unmanned surface
vehicles (USVs) in large-scale and uncertain environments. A novel speed adaptive robust …

Deep reinforcement learning holds significant potential for application in industrial decision-
making, offering a promising alternative to traditional physical models. However, its black …