Aiming at the shortcomings of the basic RRT algorithm, such as the random search ability is
relatively strong, and the calculation result is usually not the shortest path, etc., an improved …

In this paper we propose a Reinforcement Learning (RL) algorithm for path tracking of a real
car-like robot. The RL network is trained in simulation and then evaluated on a small racing …

Path planning is an important function for executing autonomous moving robots, and many
path planning methods that satisfy various constraints, such as avoiding obstacles and …

The importance of last-mile delivery (LMD) in today's logistics networks has increased
recently due to the rising popularity of e-commerce and home delivery. Various LMD modes …

Worldwide, the use of mobile robot has been growing rapidly. In aerospace, for instance,
mobile robot have become ubiquitous in both military and civilian applications. Today, for …

The path planning is one of the hottest issues of the mobile robotics, which is to find an
optimized path for the robot to reach the target location from a start position. In this research …

In this paper, we propose a new methodology to embed deep learning-based algorithms in
both visual recognition and motion planning for general mobile robotic platforms. A …

One of the key requirements of autonomous mobile robots is a robust and accurate
localisation system. Recent advances in the development of Monte Carlo Localisation (MCL) …

Path planning is one of the research hotspots for outdoor mobile robots. This paper
addresses the issues of slow convergence and low accuracy in the Double Deep Q Network …

To enable an autonomous mobile robot to navigate safely in a dy-namic environment, the
mobile robot must address four typical functional blocks of the navigation system including …