Diplomandenseminar

 -  11:15 Uhr
Kolloquium

Data driven modeling and optimal manipulator control

von: Adriano del Río Fernandez  (École Centrale de Nantes)
In the field of optimal control linear systems are generally desirable. In the case of model predictive control the benefit of a linear system representation is significant, as it implies convexity of the optimization problem and global optimality for every solution. In this context very interesting…

 -  13:00 Uhr
Kolloquium

Outdoor navigation in uneven terrain using learning methods

von: Malika Helapita  (Hochschule Bonn-Rhein-Sieg (HBRS))
The challenge of robot navigation in uneven outdoor environments is demanding but important application for outdoor mobile robots. Classical geometric approaches have been employed to solve this problem but with limited success. When the terrain becomes exceedingly irregular or if there are tall gra…

 -  13:00 Uhr
Kolloquium
Guiding exploration of the environment via disagreement is a common approach in model-based ensemble learning methods. For the effectiveness of the approach, the ensemble diversity is a crucial property. In this work, we investigate the usage of a state-of-the-art multi-modal optimizer to generate a…

 -  13:00 Uhr
Kolloquium
Eine wiederkehrende Herausforderung bei Exoskeletten ist die Übertragung von Kräften und Momenten entlang virtueller Achsen, welche sich im menschlichen Körper befinden. Ein Beispiel hierfür ist die Rotation des Beines um dessen Längsachse. Dieser Freiheitsgrad wird von vielen Exoskeletten nicht abg…

 -  14:00 Uhr
Kolloquium

Control Strategies for a Rimless Wheel Micro-Rover

von: Dennis Schlee  (TU Darmstadt)
Rimless wheeled robots are a hybrid variant of traditionally wheeled and legged robots. These hybrid systems combine the benefits of both approaches, such as efficient power demands and good terrain traversability. However, the simplicity of the design of the rimless wheel has the disadvantage of li…

 -  13:30 Uhr
Exposé
Controlling highly dynamic systems, such as legged robots, can be a very challenging task and requires a lot of computational resources. Most modern control architectures use state-of-the-art control strategies involving Model Predictive Control (MPC). These controllers require an underlying Quadrat…

 -  14:30 Uhr
Zwischenbericht
Bipedal and quadruped robots are advancing rapidly, showcasing remarkable abilities in traversing complex terrains and executing diverse tasks. Central to their performance is the accurate detection of foot-toground contact, crucial for maintaining stability and balance. Particularly in challenging …

 -  14:00 Uhr
Zwischenbericht
Autonomous micro-rovers offer a cost-effective approach for exploring lunar lava tubes and play an essential role in on-site operations. However, lunar rovers encounter significant challenges, including prolonged darkness and constrained resources. These constraints encompass factors such as process…

 -  13:30 Uhr
Zwischenbericht
Dynamic legged locomotion is a challenging control task in modern robotics, as the body is underactuated during many gaits and the contact forces of the feet are constraint due to motor limits and friction forces. A modern approach to tackle these challenges is Model Predictive Control (MPC) where t…

 -  13:00 Uhr
Exposé
Selbst lernende Roboter gewinnen zunehmend an Bedeutung. Zentraler Treiber dieser Entwicklung ist die Verbesserung zugrundeliegender Reinforcement Learning Algorithmen. Neben der Lerngeschwindigkeit ist auch die effiziente Nutzung bereitgestellter Rechenkapazitäten zur Simulation physikalisch möglic…

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zuletzt geändert am 31.03.2023