Benjamin Inden, Yaochu Jin, Robert Haschke, Helge Ritter,
"Exploiting inherent regularity in control of multilegged robot locomotion by evolving neural fields",
Third World Congress on Nature and Biologically Inspired Computing, pp. 401-408, 2011.
Abstract
The control of multilegged robots is challenging because of the large number of sensors and actuators involved. However, the regularity inherent to gait control can be taken into account to design controllers for multilegged robots. In this paper, we show that NEATfields, a method designed for the evolution of large neural networks, can exploit this regularity to evolve significantly better gaits than those evolved by the standard NEAT method. We...
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Jörg Bornschein, Marc Henniges, Gervasio Puertas, Jörg Lücke,
"Sparse codes of V1 simple-cells and the emergence of globular receptive fields - a comparative study",
Cosyne 2011, 2011.
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Robert Kastner, Tobias Kühnl, Jannik Fritsch, Christian Goerick,
"Detection and motion estimation of moving objects based on 3D-Warping",
IEEE Intelligent Vehicles Symposium (IV), 2011.
Abstract
The detection of objects in the surrounding environment is a key functionality for every Advanced Driver Assistance System (ADAS). Otherwise, it is impossible to realize any kind of advanced assistance functionality as e.g. a Forward Collision Warning. Besides static obstacles that limit the drivable area, dynamic objects can even be more dangerous due to their ego-movement. Therefore, a detection and also motion estimation of moving objects in t...
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Cem Karaoguz, Tobias Rodemann, Britta Wrede,
"Optimisation of Gaze Movement for Multitasking Using Rewards",
International Conference on Intelligent Robot and Systems (IROS 2011), 2011.
Abstract
Domestic tasks such as grasping or navigation for robotic systems can be supported by vision. However, the environment provides a vast amount of visual information and concentrating on the information related to the task being undertaken is an important job. Active vision is an approach that provides such a ltering mechanism by using camera movements to bring relevant information into the focus of attention. However timing of gaze shifts (i.e. wh...
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Qiang Li, Robert Haschke, Helge Ritter, Bram Bolder,
"Preliminary Result of Unknown Object Manipulation Based on Reactive Control",
IEEE Int. Conf. on Robotics and Biomimetics (ROBIO), 2011.
Abstract
In this paper, the authors proposed a novel reactive strategy to solve a unknown object local manipulation problem with an multingered robot hand. In this method, the micro manipulation assumption is proposed and the object can be manipulated within the robot hand workspace without the active and explicit controlling about the rolling and sliding of the ngertips on the object. A 6 D.O.F reactive controller based on the hybrid of the contact force...
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Raphael Golombek, Sebastian Wrede, Marc Hanheide, Martin Heckmann,
"On-line Data-Driven Fault Detection for Robotic Systems",
Proc. Int. Conf. Intell. Robots and Systems (IROS), 2011.
Abstract
In this paper we demonstrate the on-line applica- bility of the fault detection and diagnosis approach which we developed earlier [1]. In previous work we showed that a purely data driven fault detection approach can be successfully built upon inter-component communication data of a robotic system and used for a-posteriori fault detection. Here we propose an extension to this approach which is capable of on-line learning of the fault model as wel...
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Marc-Oliver Gewaltig, Abigail Morrison, Hans Plesser,
"NEST by example: an introduction to the neural simulation tool NEST",
Computational Systems Biology, Springer, 2011.
Abstract
The neural simulation tool NEST can simulate small to very large networks of point-neurons or neurons with a few compartments. In this chapter, we show by example how models are programmed and simulated in NEST....
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Edgar Reehuis, Johannes Kruisselbrink, Markus Olhofer, Lars Gräning, Bernhard Sendhoff, Thomas Bäck,
"Model Guided Evolution Strategies for Dynamically Balancing Exploration and Exploitation",
The Biannual International Conference on Articial Evolution, pp. 306-317, 2011.
Abstract
Wide exploration of high-dimensional, multimodal design spaces is required for uncovering alternative solutions in the conceptual phase of design optimization tasks. We present a general framework for balancing exploration and exploitation during the course of the optimiza- tion that induces sequential exploitation of different optima in the search space by selecting on a solution’s fitness and a dynamic criterion termed interestingness. We use...
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Ulf Großekathöfer, Alexandra Barchunova, Thomas Hermann, Stefan Kopp, Robert Haschke, Mathias Franzius, Helge Ritter,
"Learning of Object Manipulation Operations from Continuous Multimodal Input",
Int. Conf. on Advanced Robotics (*IEEE-RAS International Conference on Humanoids) (ICAR), pp. 507-5012, 2011.
Abstract
In this paper we propose an approach for identification of high-level object manipulation operations within a continuous multimodal time-series. We focus on multimodal approach for robust recognition of action primitive data. Our procedure combines an unsupervised Bayesian multimodal segmentation with a supervised machine learning approach. We briefly outline (1) the unsupervised segmentation and selection of uni- and bi- manual manipulation prim...
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Andreas Alin, Martin Butz, Jannik Fritsch,
"Tracking Moving Vehicles Using an Advanced Grid-based Bayesian Filter Approach",
IEEE Intelligent Vehicles Symposium (IV), 2011.
Abstract
Neuroscientific research suggests that the human brain encodes spatial information in a Bayesian-optimal way by means of distributed, neural population codes. In this paper we apply this concept to Advanced Driver Assistance Systems, introducing a grid-based population code for tracking and predicting the behavior of individual vehicles. The representation encodes a spatially distributed hidden Markov model of current and future vehicle locations...
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