5 accepted papers
Person re-identification plays a key role in applications where a mobile robot needs to track its users over a long period of time, even if they are partially unobserved for some time, in order to follow them or be available on demand. In this context, deep-learning-based real-time feature extractio…
With the emergence of collaborative robots (cobots), human-robot collaboration in industrial manufacturing is coming into focus. For a cobot to act autonomously and as an assistant, it must understand human actions during assembly. To effectively train models for this task, a dataset containing suit…
Automated grasping of arbitrary objects is an essential skill for many applications such as smart manufacturing and human robot interaction. This makes grasp detection a vital skill for automated robotic systems. Recent work in model-free grasp detection uses point cloud data as input and typically…
This paper introduces a novel robot-based approach to the stroke rehabilitation scenario, in which a mobile robot companion accompanies stroke patients during their walking self-training. This assistance enables them to move freely in the clinic practicing both their mobility and spatial orientation…
Rehabilitative follow-up care is important for stroke patients to regain their motor and cognitive skills. We aim to develop a robotic rehabilitation assistant for walking exercises in late stages of rehabilitation. The robotic rehab assistant is to accompany inpatients during their self-training, p…