Most Cited

Recent technological advances enable gripper-equipped robots to perform many tasks traditionally associated with the human hand, allowing the use of grippers in a wide range of applications. Depending on the application, an ideal gripper design shoul...

The most important research area in robotics is navigation algorithms. Robot path planning (RPP) is the process of choosing the best route for a mobile robot to take before it moves. Finding an ideal or nearly ideal path is referred to as “path...

Recently, with the in-depth development of Industry 4.0 worldwide, mobile robots have become a research hotspot. Indoor localization has become a key component in many fields and the basis for all actions of mobile robots. This paper screened 147 pap...

This study provides a structured literature review of the recent COllaborative roBOT (COBOT) applications in industrial and service contexts. Several papers and research studies were selected and analyzed, observing the collaborative robot interactio...

Automation and robotics are the key players in modern agriculture. They offer potential solutions for challenges related to the growing global population, demographic shifts, and economic status. This review paper evaluates the challenges and opportu...

This research proposes a robust nonlinear hybrid control approach to the speed control of a multi-input-and-multi-output separately excited DC motor (SEDCM). The motor that was under consideration experienced parametric uncertainties and load disturb...

Recently, the need to produce from soft materials or components in extra-large sizes has appeared, requiring special solutions that are affordable using industrial robots. Industrial robots are suitable for such tasks due to their flexibility, accura...

This literature review presents a comprehensive analysis of the use and potential application scenarios of collaborative robots in the industrial working world, focusing on their impact on human work, safety, and health in the context of Industry 4.0...

Deep reinforcement learning (DRL) has been demonstrated to be effective for several complex decision-making applications, such as autonomous driving and robotics. However, DRL is notoriously limited by its high sample complexity and its lack of stabi...

In recent years, deep learning techniques for processing 3D point cloud data have seen significant advancements, given their unique ability to extract relevant features and handle unstructured data. These techniques find wide-ranging applications in...