Deep reinforcement learning (RL) has shown promising results in the motion planning of
manipulators. However, no method guarantees the safety of highly dynamic obstacles, such …

Industrial collaborative robotics is promising for manufacturing activities where the presence
of a robot alongside a human operator can improve operator's working conditions, flexibility …

Strategies for safe human-robot interaction (HRI), such as the well-established Safe Motion
Unit, provide a velocity scaling for biomechanically safe robot motion. In addition …

Collaborative robots have to adapt its motion plan to a dynamic environment and variation of
task constraints. Currently, they detect collisions and interrupt or postpone their motion plan …

We propose a safety control approach based on the online optimal scaling of the size of
bounding volumes used as dynamic safety zones for collaborative robotics. Intersection tests …

In this paper, a novel approach for the application of dynamic safety zones based on the
requirements of safety standards for collaborative robotics is presented. The aim of the …

Current safety mechanisms implementing industry standards for human-robot coexistence
separate humans and robots through caging. Other approaches allowing humans to enter …

In the model predictive control formulations of trajectory tracking problems, infeasible
reference trajectories and a priori unknown constraints can lead to cumbersome designs …

Deep reinforcement learning (RL) has shown promising results in robot motion planning
with first attempts in human-robot collaboration (HRC). However, a fair comparison of RL …

The advent of mass customization has precipitated a need within the industry for the
implementation of collaborative robots, which facilitate the integration of human cognitive …