With the advent of Industry 4.0, several cutting-edge technologies such as cyber-physical
systems, digital twins, IoT, robots, big data, cloud computation have emerged. However, how …

When a natural or human disaster occurs, time is critical and often of vital importance. Data
from the incident area containing the information to guide search and rescue (SAR) …

This paper provides a structured and practical roadmap for practitioners to integrate learning
from demonstration (LfD) into manufacturing tasks, with a specific focus on industrial …

Existing Visual Simultaneous Localization And Mapping (vSLAM) approaches that offload
the complex self-localization computations from mobile robots over a wireless network to …

With the wide deployment of autonomous multi-agent robotic systems, control solutions
based on centralized algorithms have been developed. Even though these centralized …

Robot vacuum cleaners have gained widespread popularity as household appliances. One
significant challenge in enhancing their functionality is to identify and classify small indoor …

The advent of new computing and communication trends that link pervasive data sources
and consumers, such as Edge Computing, 5G and IIoT, has led to the development of the …

Deep reinforcement learning (DRL) is one of the most powerful tools for synthesizing
complex robotic behaviors. But training DRL models is incredibly compute and memory …

In recent years, the need for resources for handling processes with high computational
complexity for mobile robots is becoming increasingly urgent. More specifically, robots need …

Future robotics systems aiming for true autonomy must be robust against dynamic and
unstructured environments. The 5th generation (5G) mobile network is expected to provide …