4 accepted papers
Robustness against specific kinds of noise is of high importance for safety-critical components in industrial robot applications, as legal and normative regulations demand the identification and handling of all unacceptable risks. This includes risks from environmental conditions, like noisy data. O…
Obtaining reliable detections of a human is crucial for many safety-related robotic tasks. This can be done by human pose estimation methods, which predict the position of several different keypoints of the human body. In most cases, recent approaches based on neural networks produce ‘good’ results,…
In the industrial domain, the application of any system as a safety function has to follow strict rules and requirements, defined in safety standards such as ISO 13849 [1] and ISO 13855 [2]. Two core requirements are an extremely low rate of dangerous errors and an upper limit for the response time…
In recent years, human pose estimation has seen great improvements by the use of neural networks. However, these approaches are unsuitable for safety-critical applications such as human-robot interaction (HRI), as no guarantees are given whether a produced detection is correct or not and false detec…