Daniel F. B. Haeufle

Orcid: 0000-0002-3480-6892

According to our database1, Daniel F. B. Haeufle authored at least 36 papers between 2012 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
HOIMotion: Forecasting Human Motion During Human-Object Interactions Using Egocentric 3D Object Bounding Boxes.
IEEE Trans. Vis. Comput. Graph., November, 2024

HaHeAE: Learning Generalisable Joint Representations of Human Hand and Head Movements in Extended Reality.
CoRR, 2024

GazeMotion: Gaze-guided Human Motion Forecasting.
CoRR, 2024

Generating Realistic Arm Movements in Reinforcement Learning: A Quantitative Comparison of Reward Terms and Task Requirements.
CoRR, 2024

Learning to Control Emulated Muscles in Real Robots: Towards Exploiting Bio-Inspired Actuator Morphology.
CoRR, 2024

Identifying Policy Gradient Subspaces.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

ATARO: A Muscle-Driven Biorobotic Arm to Investigate Healthy and Impaired Motor Control.
Proceedings of the 10th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics, 2024

Learning to Control Emulated Muscles in Real Robots: A Software Test Bed for Bio-Inspired Actuators in Hardware.
Proceedings of the 10th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics, 2024

Quantifying Human Upper Limb Stiffness Responses Based on a Computationally Efficient Neuromusculoskeletal Arm Model.
Proceedings of the 10th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics, 2024

Supporting Functional Tasks in Bi-Manual Robotic Mirror Therapy by Coupling Upper Limb Movements Based on Virtual Reality.
Proceedings of the 10th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics, 2024

Generating Realistic Arm Movements in Reinforcement Learning: A Quantitative Comparison of Reward Terms and Task Requirements.
Proceedings of the 10th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics, 2024

2023
A Commentary on <i>Towards autonomous artificial agents with an active self: Modeling sense of control in situated action</i>.
Cogn. Syst. Res., June, 2023

Investigating the Impact of Action Representations in Policy Gradient Algorithms.
CoRR, 2023

Natural and Robust Walking using Reinforcement Learning without Demonstrations in High-Dimensional Musculoskeletal Models.
CoRR, 2023

DEP-RL: Embodied Exploration for Reinforcement Learning in Overactuated and Musculoskeletal Systems.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Virtual pivot point in human walking: always experimentally observed but simulations suggest it may not be necessary.
CoRR, 2022

Slack-based tunable damping leads to a trade-off between robustness and efficiency in legged locomotion.
CoRR, 2022

Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks.
Proceedings of the Conference on Robot Learning, 2022

2021
Correction to: A geometry- and muscle-based control architecture for synthesising biological movement.
Biol. Cybern., 2021

A geometry- and muscle-based control architecture for synthesising biological movement.
Biol. Cybern., 2021


2020
Effective Viscous Damping Enables Morphological Computation in Legged Locomotion.
Frontiers Robotics AI, 2020

Muscles Reduce Neuronal Information Load: Quantification of Control Effort in Biological vs. Robotic Pointing and Walking.
Frontiers Robotics AI, 2020

Morphological Computation Increases From Lower- to Higher-Level of Biological Motor Control Hierarchy.
Frontiers Robotics AI, 2020

Optimality Principles in Human Point-to-Manifold Reaching Accounting for Muscle Dynamics.
Frontiers Comput. Neurosci., 2020

Simulating the response of a neuro-musculoskeletal model to assistive forces: implications for the design of wearables compensating for motor control deficits.
Proceedings of the 8th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics, 2020

2018
The Benefit of Combining Neuronal Feedback and Feed-Forward Control for Robustness in Step Down Perturbations of Simulated Human Walking Depends on the Muscle Function.
Frontiers Comput. Neurosci., 2018

Bioinspired pneumatic muscle spring units mimicking the human motion apparatus: benefits for passive motion range and joint stiffness variation in antagonistic setups.
Proceedings of the 25th International Conference on Mechatronics and Machine Vision in Practice, 2018

Learning to Control Redundant Musculoskeletal Systems with Neural Networks and SQP: Exploiting Muscle Properties.
Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

2016
Evaluating Morphological Computation in Muscle and DC-Motor Driven Models of Hopping Movements.
Frontiers Robotics AI, 2016

2015
Evaluating Morphological Computation in Muscle and DC-motor Driven Models of Human Hopping.
CoRR, 2015

Musculo-Skeletal Models as Tools to Quantify Embodiment.
Proceedings of the Thirteenth European Conference Artificial Life, 2015

2013
Theoretical Hill-Type Muscle and Stability: Numerical Model and Application.
Comput. Math. Methods Medicine, 2013

2012
Spreading out Muscle Mass within a Hill-Type Model: A Computer Simulation Study.
Comput. Math. Methods Medicine, 2012

Energy management that generates terrain following versus apex-preserving hopping in man and machine.
Biol. Cybern., 2012

Can Robots Help to Understand Human Locomotion?
Autom., 2012


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