Path planning algorithms generally require several steps including mapping, localization,
sensor data processing, etc. Deep learning-based approach has been proposed to achieve …

The study addresses path planning problems for autonomous mobile robots (AMRs),
considering their kinematics, where performance and responsiveness are often …

Autonomous mobile robots are essential to the industry, and human–robot interactions are
becoming more common nowadays. These interactions require that the robots navigate …

Due to the limitation of mobile robots' understanding of the environment in local path
planning tasks, the problems of local deadlock and path redundancy during planning exist in …

This paper investigates the optimization problem of scheduling autonomous mobile robots
(AMRs) in hospital settings, considering dynamic requests with different priorities. The …

This paper proposes a navigation scheme for robots in indoor environments which uses real-
time analysis of raw data captured by an infra-red sensor. The infra-red sensor captures …

Moving in complex environments is an essential capability of intelligent mobile robots.
Decades of research and engineering have been dedicated to developing sophisticated …

This paper presents a supervised learning approach to improving the autonomous mobility
of wheeled robots through sensing the robot's interaction with terrain 'underfoot.'Mobility …

Feasible local motion planning for autonomous mobile robots in dynamic environments
requires predicting how the scene evolves. Conventional navigation stakes rely on a local …

Autonomous mobile robots have become integral to daily life, providing crucial services
across diverse domains. This paper focuses on path following, a fundamental technology …