Providing mobile robots with autonomous capabilities is advantageous. It allows one to
dispense with the intervention of human operators, which may prove beneficial in economic …

Principles of typical motion planning algorithms are investigated and analyzed in this paper.
These algorithms include traditional planning algorithms, classical machine learning …

Mobile robot path planning in an unknown environment is a fundamental and challenging
problem in the field of robotics. Dynamic window approach (DWA) is an effective method of …

Intelligent vehicles have increased their capabilities for highly and, even fully, automated
driving under controlled environments. Scene information is received using onboard …

Motion planning is a fundamental research area in robotics. Sampling-based methods offer
an efficient solution for what is otherwise a rather challenging dilemma of path planning …

During the last decade, sampling-based path planning algorithms, such as probabilistic
roadmaps (PRM) and rapidly exploring random trees (RRT), have been shown to work well …

The prospect of driverless cars wide-scale deployment is imminent owing to the advances in
robotics, computational power, communications, and sensor technologies. This promises …

In this paper, we present Batch Informed Trees (BIT*), a planning algorithm based on
unifying graph-and sampling-based planning techniques. By recognizing that a set of …

When mobile robot used in large-scale dynamic environments, it face more challenging
problems in real-time path planning and collision-free path tracking. This paper presents a …

The Rapidly-exploring Random Tree (RRT) algorithm, based on incremental sampling,
efficiently computes motion plans. Although the RRT algorithm quickly produces candidate …