Folgen
Daniel Tanneberg
Daniel Tanneberg
Senior Scientist @ Honda Research Institute EU, PhD from IAS @ TU Darmstadt
Bestätigte E-Mail-Adresse bei robot-learning.de
Titel
Zitiert von
Zitiert von
Jahr
Recurrent spiking networks solve planning tasks
E Rueckert, D Kappel, D Tanneberg, D Pecevski, J Peters
Scientific reports 6 (1), 21142, 2016
842016
SKID RAW: Skill Discovery from Raw Trajectories
D Tanneberg, K Ploeger, E Rueckert, J Peters
IEEE Robotics and Automation Letters 6 (3), 4696 - 4703, 2021
322021
Intrinsic Motivation and Mental Replay enable Efficient Online Adaptation in Stochastic Recurrent Networks
D Tanneberg, J Peters, E Rueckert
Neural Networks 109, 67-80, 2019
312019
LaMI: Large Language Models for Multi-Modal Human-Robot Interaction
C Wang, S Hasler, D Tanneberg, F Ocker, F Joublin, A Ceravola, ...
Extended Abstracts of the CHI Conference on Human Factors in Computing …, 2024
30*2024
CoPAL: corrective planning of robot actions with large language models
F Joublin, A Ceravola, P Smirnov, F Ocker, J Deigmoeller, A Belardinelli, ...
2024 IEEE International Conference on Robotics and Automation (ICRA), 8664-8670, 2024
272024
Model-Based Quality-Diversity Search for Efficient Robot Learning
L Keller, D Tanneberg, S Stark, J Peters
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020
252020
Explainable human-robot training and cooperation with augmented reality
C Wang, A Belardinelli, S Hasler, T Stouraitis, D Tanneberg, M Gienger
Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing …, 2023
222023
Generalized exploration in policy search
H van Hoof, D Tanneberg, J Peters
Machine Learning 106 (9), 1705-1724, 2017
212017
Intention estimation from gaze and motion features for human-robot shared-control object manipulation
A Belardinelli, AR Kondapally, D Ruiken, D Tanneberg, T Watabe
2022 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2022
152022
Deep spiking networks for model-based planning in humanoids
D Tanneberg, A Paraschos, J Peters, E Rueckert
2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids …, 2016
122016
Evolutionary training and abstraction yields algorithmic generalization of neural computers
D Tanneberg, E Rueckert, J Peters
Nature Machine Intelligence 2 (12), 753-763, 2020
72020
To Help or Not to Help: LLM-based Attentive Support for Human-Robot Group Interactions
D Tanneberg, F Ocker, S Hasler, J Deigmoeller, A Belardinelli, C Wang, ...
2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024
62024
Simulation of the underactuated Sake Robotics Gripper in V-REP
SK Thiem, S Stark, D Tanneberg, J Peters, E Rueckert
Workshop at 2017 IEEE-RAS 17th International Conference on Humanoid Robotics …, 2017
62017
Learning type-generalized actions for symbolic planning
D Tanneberg, M Gienger
2023 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2023
52023
Online learning with stochastic recurrent neural networks using intrinsic motivation signals
D Tanneberg, J Peters, E Rueckert
Conference on Robot Learning, 167-174, 2017
52017
Learning Algorithmic Solutions to Symbolic Planning Tasks with a Neural Computer Architecture
D Tanneberg, E Rueckert, J Peters
arXiv preprint arXiv:1911.00926, 2019
4*2019
Tulip Agent--Enabling LLM-Based Agents to Solve Tasks Using Large Tool Libraries
F Ocker, D Tanneberg, J Eggert, M Gienger
arXiv preprint arXiv:2407.21778, 2024
32024
Efficient Online Adaptation with Stochastic Recurrent Neural Networks
D Tanneberg, J Peters, E Rueckert
2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids …, 2017
32017
Personalized brain-computer interfaces for non-laboratory environments
T Friess, KH Fiebig, D Sharma, N Faber, T Hesse, D Tanneberg, J Peters, ...
Cybathlon Symposium, Zürich, 2016
32016
Open-Ended Learning of Grasp Strategies using Intrinsically Motivated Self-Supervision
Q Delfosse, S Stark, D Tanneberg, VG Santucci, J Peters
Workshop at the International Conference on Intelligent Robots and Systems …, 2019
12019
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–20