Ahmet Ercan Tekden
Ahmet Tekden is a PhD student in the Automatic Control research group. His research project is "Data-efficient Representation Learning for Robot Grasping and Manipulation".
His research interests lie in representation learning and robotic manipulation. In particular, he is interested in pursuing the research question of how an agent should interact with its environment so that it can learn underlying structured models of the environment that can be used in various manipulation tasks.
Ahmet Tekden is a WASP affiliated PhD student.
Showing 8 publications
Grasp Transfer based on Self-Aligning Implicit Representations of Local Surfaces
Data-Efficient Representation Learning for Grasping and Manipulation
Object and relation centric representations for push effect prediction
Grasp Transfer based on Self-Aligning Implicit Representations of Local Surfaces
Sliding Touch-Based Exploration for Modeling Unknown Object Shape with Multi-Fingered Hands
Neural Field Movement Primitives for Joint Modelling of Scenes and Motions
Neural Field Movement Primitives for Joint Modelling of Scenes and Motions
Affordance Transfer based on Self-Aligning Implicit Representations of Local Surfaces
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