7 citations · 25 across the 9 of their papers we have counts for
11 papers
The influence of labeling techniques in classifying human manipulation movement of different speed
Sadique Adnan Siddiqui, Lisa Gutzeit, Frank Kirchner
In this work, we investigate the influence of labeling methods on the classification of human movements on data recorded using a marker-based motion capture system. The dataset is…
Grasp stability prediction with time series data based on STFT and LSTM
Tao Wang, Frank Kirchner
With an increasing demand for robots, robotic grasping will has a more important role in future applications. This paper takes grasp stability prediction as the key technology for…
Design, analysis and control of the series-parallel hybrid RH5 humanoid robot
Julian Esser, Shivesh Kumar, Heiner Peters +5
Last decades of humanoid research has shown that humanoids developed for high dynamic performance require a stiff structure and optimal distribution of mass--inertial properties. H…
Are Gradient-based Saliency Maps Useful in Deep Reinforcement Learning?
Matthias Rosynski, Frank Kirchner, Matias Valdenegro-Toro
Deep Reinforcement Learning (DRL) connects the classic Reinforcement Learning algorithms with Deep Neural Networks. A problem in DRL is that CNNs are black-boxes and it is hard to…
Black-Box Optimization of Object Detector Scales
Mohandass Muthuraja, Octavio Arriaga, Paul Plöger +2
Object detectors have improved considerably in the last years by using advanced CNN architectures. However, many detector hyper-parameters are generally manually tuned, or they are…
Perception for Autonomous Systems (PAZ)
Octavio Arriaga, Matias Valdenegro-Toro, Mohandass Muthuraja +2
In this paper we introduce the Perception for Autonomous Systems (PAZ) software library. PAZ is a hierarchical perception library that allow users to manipulate multiple levels of…