Path planning is an important part of the navigation control system of mobile robots since it
plays a decisive role in whether mobile robots can realize autonomy and intelligence. The …

Artificial potential field has long been proposed in the field of robot path planning. But the
well-known drawbacks like local minimal problem and low efficiency prevent its wide …

As a challenging optimization problem, path planning for mobile robot refers to searching an
optimal or near-optimal path under different types of constrains in complex environments. In …

This paper presents an effective improved artificial potential field-based regression search
(improved APF-based RS) method that can obtain a better and shorter path efficiently …

Mobile robot path planning is a key technology and challenge in robot automation field. For
a long time, particle swarm optimization has been used in path planning, while the well …

In this paper, an improved artificial potential field method is proposed to address the
problems of excessive gravitational force, unachievable goal, and falling into concave …

The existing particle swarm optimization (PSO) algorithm has the disadvantages of
application limitations and slow convergence speed when solving the problem of mobile …

The artificial potential field method is used in mobile robot path planning extensively
because of its simpleness, high efficiency and smooth path, but it also has its disadvantages …

Aiming at the problems of the A* algorithm in mobile robot path planning, such as multiple
nodes, low path accuracy, long running time and difficult path initialization of particle swarm …

Mobile robots are becoming more and more widely used in industry and life, so the
navigation of robots in dynamic environments has become an urgent problem to be solved …