Automation is increasingly at the forefront of transportation research, with the potential to
bring fully autonomous vehicles to our roads in the coming years. This comprehensive …

Recent years have seen a dramatic rise in the popularity of autonomous mobile robots
(AMRs) due to their practicality and potential uses in the modern world. Path planning is …

Automatic path planning problem is essential for efficient mission execution by unmanned
aerial vehicles (UAVs), which needs to access the optimal path rapidly in the complicated …

The recent proliferation of computing technologies (eg, sensors, computer vision, machine
learning, and hardware acceleration) and the broad deployment of communication …

Reinforcement learning (RL) is a promising approach in unmanned ground vehicles (UGVs)
applications, but limited computing resource makes it challenging to deploy a well-behaved …

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

This article presents a novel path planning algorithm for autonomous land vehicles. There
are four main contributions: Firstly, an evaluation standard is introduced to measure the …

Autonomous navigation of a robot is a promising research domain due to its extensive
applications. The navigation consists of four essential requirements known as perception …

A defining feature of sampling-based motion planning is the reliance on an implicit
representation of the state space, which is enabled by a set of probing samples …

Sampling-based model-predictive control (MPC) is a promising tool for feedback control of
robots with complex, non-smooth dynamics, and cost functions. However, the …