PyTorch

Render of the slip-detection teststand with linear actuator and sensor stack

Visuo-Tactile Slip Detection for Teleoperated Manipulation

Master’s research at TU Darmstadt: a multi-sensor teststand and neural networks for detecting and regressing slip in robotic grippers.

Overview of the bin-picking system: robot cell, part bins, and processing pipeline

Bachelor Thesis — Robotic Bin-Picking via Supervised and Imitation Learning

Neural network-based part selection for semi-autonomous bin-picking of radioactive waste, trained on VR teleoperation data. 73% grasp accuracy at +1.2 ms latency.

A completed AlphaZero self-play Connect Four game with move numbers, next to the MCTS policy distribution of a mid-game decision

Reinforcement Learning Agent in Games (AlphaZero)

AlphaZero-based framework that learns tic-tac-toe, Connect 4, and CartPole with a unified model architecture.