Diplomandenseminar

Die AG Robotik von der Universität Bremen bietet in Kooperation mit dem Robotics Innovation Center von der DFKI GmbH eine ganze Reihe von Seminaren und Vorträgen an. In dieser Reihe sind die Bachelor-, Master- und Diplomarbeiten enthalten. Die Termine werden hier regelmäßig aktualisiert. Externe können in vielen Fällen nach Rücksprache mit dem Sekretariat an den Vorträgen teilnehmen.

Vorträge

 -  13:30 Uhr
Zwischenbericht

Reinforcement Learning-based Control for Swing-up and Stabilization of an Underactuated Double Pendulum System

von: Chi Zhang  (Technische Universität München)
The challenge of controlling nonlinear systems has sparked significant interest within the research community. In particular, reinforcement learning-based control methods present promising advantages for addressing nonlinear control challenges, including reduced reliance on detailed system models an…
 -  13:00 Uhr
Exposé

Learning State Transition Functions of a Hydraulic Excavator using Data Driven Deep Learning

von: Jayanth Somashekaraiah  (Universität Bremen)
In this thesis, a neural network model is trained to learn the state transition function of a hydraulic excavator arm or a crane using data driven approach. The excavator arm or crane exhibits highly non linear behaviour due to hydraulic coupling between its actuators, non linearities in valves, par…
 -  13:00 Uhr
Kolloquium

Detection and Autonomous Following of Divers of Divers Utilizing Forward Looking Sonar

von: Samin Yasar Haque  (Constructor University Bremen)
Final presentation: Imaging sonar is commonly used in underwater detection tasks, as it can provide acoustic imaging of underwater environments in low or zero visibility conditions where optical sensors fail. The forward-looking sonar (FLS) is commonly used for monitoring tasks due to its capabilit…
 -  14:00 Uhr
DFKI Vortrag

Autonomy in marine robotics - AI or automation?

von: Dr. Leif Christensen
BBT CIMATEC & DFKI | 2. JOINT TECH SESSION
 -  13:30 Uhr
Zwischenbericht

Evaluation of metrics for human-like grips

von: Florian Seidler  (Universität Bremen)
For each grasp, there are a large number of possible contact points with different properties. The quality of grasps can be determined using metrics. Metrics are tools that can be used to measure a specific characteristic of a process.  To mimic human grasping, these metrics could be used. Howe…
 -  13:00 Uhr
Zwischenbericht

Ambient Air Pollution Prediction

von: Hannes Gelbhardt  (Universität Bremen)
Ambient air pollution is well known to affect humans and the environment severely. Some primary sources of air pollution are industrial processes, motorized traffic, wildfires, and volcanic activities. Estimating future air pollution concentrations can lower the effects on humans and the environment…
 -  13:00 Uhr
Zwischenbericht

Model Predictive Controller for 3-dof free floating platform with binary actuated thrusters and reaction wheel

von: Franek Stark  (Universität Bremen)
Air-bearing-based platforms are used to simulate microgravity on Earth. Therefore, these platforms can be used to test for example Active Space Debris Removal (ASDR) maneuvers. European Space Agency’s Orbital Robotics and GNC Lab (ORGL) features a 5m × 9m flat floor. A 220 kg heavy air-bearing platf…
 -  14:00 Uhr
Kolloquium

Mechatronic Design and Control of an Underactuated Three-link Brachiation Robot

von: Shourie Grama Srinivas  (École Centrale de Nantes, Nantes, France)
Brachiation is a type of locomotion achieved by swinging from place to place, employed by Monkeys (mostly Gibbons). During brachiation, if the Gibbon encounters a distant branch such that it is expected to have a dynamic free flight phase in its motion, this rapid motion mode is called 'Fast Brachia…
 -  13:30 Uhr
Exposé

Adversary-driven Exploration in Coordinative Multi-Agent Deep Reinforcement Learning

von: Tim Schnauder  (Universität Bremen)
Multi-agent deep reinforcement learning (MADRL) is a powerful approach that enables agents to coordinate and collaborate to solve complex collaborative tasks. Applications of MADRL range from robotics to traffic control and resource allocation. However, the learning process can be slow, especially w…
 -  12:30 Uhr
Exposé

Robot state estimation using Synthetic RGB images

von: Vasantakumaar, Naren  (Universität Bremen)
The aim of this thesis is to use a camera as a cost-effective alternative to the expensive retrofitting of sensors for state estimation of the manipulator. Determining the state of robot joints from images has always been a challenge in the field of computer vision and robotics. Thus, determining th…
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zuletzt geändert am 06.09.2024