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

 -  14:00 Uhr
Zwischenbericht

Hybrid-Driven State Estimation for a Humanoid Robot

von: Lasse Hohmeyer  (Universität Bremen)
State estimation refers to all algorithms calculating the internal state of a robot. Since the true state is always unknown, it has to be estimated based on a series of noisy and inaccurate measurements. This is a crucial task in mobile robotics and a more accurate state estimation almost always lea…
 -  13:00 Uhr
Kolloquium

Enhancing Human-Robot Dialogue with Visual Voice Activity Detection

von: Arunima Gopikrishnan  (Universität Bremen)
This thesis critically examines the integration of Visual Voice Activity Detection (VVAD) technology into human-robot dialogue systems, focusing on its potential to enhance communication in noisy environments. While traditional speech recognition systems excel in quiet settings, their performance de…
 -  13:30 Uhr
Zwischenbericht

Unified model for Grasp stability estimation

von: Prithvi Sanghamreddy  (Universität Bremen)
Grasp stability is one of the main concerns in the field of robotics, as it directly impacts the effectiveness and safety of robotic manipulation tasks. Grasping an object and evaluating the grasp is an important task when we use robotic hands. Establishing robotic hands that can securely hold and m…
 -  13:00 Uhr
Exposé

Design Optimization of the RH5 Humanoid Robot for Reinforcement Learning-Driven Pull-Up Performance

von: Tianyi Jin  (RWTH Aachen)
This thesis aims to advance the design optimization of the RH5 humanoid robot to enhance performance in high-effort tasks, specifically focusing on the pull-up exercise to evaluate upper body strength and endurance. The research addresses existing limitations in upper-body research of humanoid robot…
 -  13:00 Uhr
Exposé

Entwicklung und Regelung eines zweiarmigen Oberkörper-Klimmzugroboters

von: Ahmad Baker  (Universität Bremen)
In den letzten Jahren haben humanoide Roboter große Fortschritte in der dynamischen Regelung und der Integration drehmomentstarker Elektromotoren mit geringer Getriebeuntersetzung gemacht. Neue Entwicklungen erlauben ihnen komplexe Bewegungen, die eine hohe Leistungsdichte, Koordination und Präzisio…
 -  15:30 Uhr
Kolloquium

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

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…
 -  13:00 Uhr
Kolloquium

Enhancement and Evaluation of an AUV's Docking Station Detection with Deep-Learning Based Object-Detection

von: Faraz Ahmad  (Constructor University)
Autonomous docking for underwater vehicles, especially locating the docking station, presents significant challenges for deploying sub-sea resident AUVs in exploration and monitoring tasks. To extend a fiducial marker-based docking station detection,  use of the state-of-the-art object detectio…
 -  14:00 Uhr
Exposé

Meta-Reinforcement Learning for Enhanced Generalization in Robotics

von: Lennart Heinbokel  (Universität Bremen)
This thesis aims to investigate the use of meta-reinforcement learning (meta-RL) to enhance sample efficiency in robotic systems, enabling agents to adapt to unseen tasks with fewer interactions. By employing contextual Markov Decision Processes (cMDPs) to formalize task variability, the study offer…
 -  13:00 Uhr
Kolloquium

Performance Evaluation of Quadratic Programming Solvers for Legged Robots on different Computer Architectures

von: Jakob Middelberg  (Universität Bremen)
In the past decade, the development of dynamic legged robots has gained significant traction and has produced remarkable results. Modern bipeds and quadrupeds are able to traverse difficult terrain while using various gaits and movements like walking, trotting, or jumping. Controlling those robotic …
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zuletzt geändert am 06.09.2024