Zobrazeno 1 - 10
of 52
pro vyhledávání: '"Plöger, Paul G."'
Neuromorphic computing mimics computational principles of the brain in $\textit{silico}$ and motivates research into event-based vision and spiking neural networks (SNNs). Event cameras (ECs) exclusively capture local intensity changes and offer supe
Externí odkaz:
http://arxiv.org/abs/2404.05858
An object handover between a robot and a human is a coordinated action which is prone to failure for reasons such as miscommunication, incorrect actions and unexpected object properties. Existing works on handover failure detection and prevention foc
Externí odkaz:
http://arxiv.org/abs/2402.18319
Autor:
Patel, Kevin, Kalagaturu, Vamsi, Mannava, Vivek, Selvaraju, Ravisankar, Shinde, Shubham, Bakaraniya, Dharmin, Nair, Deebul, Wasil, Mohammad, Thoduka, Santosh, Awaad, Iman, Schneider, Sven, Hochgeschwender, Nico, Plöger, Paul G.
This paper presents the b-it-bots RoboCup@Work team and its current hardware and functional architecture for the KUKA youBot robot. We describe the underlying software framework and the developed capabilities required for operating in industrial envi
Externí odkaz:
http://arxiv.org/abs/2312.17643
Autor:
Mitrevski, Alex, Plöger, Paul G.
This paper presents a modification of the data-driven sensor-based fault detection and diagnosis (SFDD) algorithm for online robot monitoring. Our version of the algorithm uses a collection of generative models, in particular restricted Boltzmann mac
Externí odkaz:
http://arxiv.org/abs/2311.13866
Loading of shipping containers for dairy products often includes a press-fit task, which involves manually stacking milk cartons in a container without using pallets or packaging. Automating this task with a mobile manipulator can reduce worker strai
Externí odkaz:
http://arxiv.org/abs/2307.08274
Saliency methods are frequently used to explain Deep Neural Network-based models. Adebayo et al.'s work on evaluating saliency methods for classification models illustrate certain explanation methods fail the model and data randomization tests. Howev
Externí odkaz:
http://arxiv.org/abs/2306.02424
State-of-the-art object detectors are treated as black boxes due to their highly non-linear internal computations. Even with unprecedented advancements in detector performance, the inability to explain how their outputs are generated limits their use
Externí odkaz:
http://arxiv.org/abs/2212.11409
In robot-assisted therapy for individuals with Autism Spectrum Disorder, the workload of therapists during a therapeutic session is increased if they have to control the robot manually. To allow therapists to focus on the interaction with the person
Externí odkaz:
http://arxiv.org/abs/2207.12144
Robots applied in therapeutic scenarios, for instance in the therapy of individuals with Autism Spectrum Disorder, are sometimes used for imitation learning activities in which a person needs to repeat motions by the robot. To simplify the task of in
Externí odkaz:
http://arxiv.org/abs/2207.12224
Autor:
Mitrevski, Alex, Thoduka, Santosh, Sáinz, Argentina Ortega, Schöbel, Maximilian, Nagel, Patrick, Plöger, Paul G., Prassler, Erwin
Robot deployment in realistic dynamic environments is a challenging problem despite the fact that robots can be quite skilled at a large number of isolated tasks. One reason for this is that robots are rarely equipped with powerful introspection capa
Externí odkaz:
http://arxiv.org/abs/2206.12719