Experience-Based Heuristic Search: Robust Motion Planning with Deep Q-Learning. - Julian Bernhard; Robert Gieselmann; Klemens Esterle; Alois C. Knoll (ITSC, 2018)

Standard Deep Generative Models for Density Estimation in Configuration Spaces: A Study of Benefits, Limits and Challenges. - Robert Gieselmann; Florian T. Pokorny (IROS, 2020)

ReForm: A Robot Learning Sandbox for Deformable Linear Object Manipulation. - Rita Laezza; Robert Gieselmann; Florian T. Pokorny; Yiannis Karayiannidis (ICRA, 2021)

Planning-Augmented Hierarchical Reinforcement Learning. - Robert Gieselmann; Florian T. Pokorny (IEEE Robotics Autom. Lett., 2021)

Conservative Definitions for Higher-order Logic with Ad-hoc Overloading. - Robert Gieselmann (2021)

Latent Planning via Expansive Tree Search. - Robert Gieselmann; Florian T. Pokorny (NeurIPS, 2022)

Expansive Latent Planning for Sparse Reward Offline Reinforcement Learning. - Robert Gieselmann; Florian T. Pokorny (CoRL, 2023)

Fast-dRRT*: Efficient Multi-Robot Motion Planning for Automated Industrial Manufacturing. - Andrey Solano; Arne Sieverling; Robert Gieselmann; Andreas Orthey (CoRR, 2023)

Synergies between Policy Learning and Sampling-based Planning ; Synergier mellan policyinlärning och sampling-baserad planering. - Robert Gieselmann (2024)