As science and technology advance rapidly, the scope of mobile robot applications
continues to expand. In mobile robotics, path planning, which has formed a relatively …

With the progress of science and technology, mobile robots gradually play an increasingly
important role in the industry, military, science and technology and other fields. Aiming at the …

Mobile robots with artificial intelligence are more and more popular on the rescue and
human-service in complex environment. Path planning techniques for robots become the …

In fact, optimizing path within short computation time still remains a major challenge for
mobile robotics applications. In path planning and obstacles avoidance, Q-Learning (QL) …

Mobile robot path planning is a key technology in the field of robotic research and
applications. Q-learning algorithm is one of the most effective methods to solve the problem …

A path planning method based on Q-learning is proposed for robot arm. As reinforcement
learning, Q-learning is widely used in the field of mobile robot navigation due to its simple …

This paper proposes an improved Q-learning algorithm for the path planning of a mobile
robot in a free-space environment. Existing Q-learning methods for path planning focus on …

Path planning in an environment with obstacles is an ongoing problem for mobile robots. Q-
learning algorithm increases its importance due to its utility in interacting with the …

How to generate the path planning of mobile robots quickly is a problem in the field of
robotics. The Q-learning (QL) algorithm has recently become increasingly used in the field of …

Path planning is a major challenging problem for mobile robots, as the robot is required to
reach the target position from the starting position while simultaneously avoiding conflicts …