Johannes Kuehn

Orcid: 0000-0003-2537-9160

According to our database1, Johannes Kuehn authored at least 11 papers between 2017 and 2023.

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

Timeline

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Links

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Bibliography

2023
A Wearable Force-Sensitive and Body-Aware Exoprosthesis for a Transhumeral Prosthesis Socket.
IEEE Trans. Robotics, June, 2023

Comparative Study of Excitation Signals for Active Fault Diagnosis of Belt Drives.
Proceedings of the 32nd IEEE International Symposium on Industrial Electronics, 2023

2022
Multisine Input Design for Active Data-Driven Fault Diagnosis of Belt Drives.
Proceedings of the 31st IEEE International Symposium on Industrial Electronics, 2022

Comparison of Different Excitation Strategies for Fault Diagnosis of Belt Drives: Industrial Application Scenarios.
Proceedings of the 19th International Conference on Informatics in Control, 2022

2021
An Integrated, Force-Sensitive, Impedance Controlled, Tendon-Driven Wrist: Design, Modeling, and Control.
Proceedings of the 20th IEEE-RAS International Conference on Humanoid Robots, 2021

2020
Observer-Extended Direct Method for Collision Monitoring in Robot Manipulators Using Proprioception and IMU Sensing.
IEEE Robotics Autom. Lett., 2020

2019
Joint Velocity and Acceleration Estimation in Serial Chain Rigid Body and Flexible Joint Manipulators.
Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

Towards Semi-Autonomous and Soft-Robotics Enabled Upper-Limb Exoprosthetics: First Concepts and Robot-Based Emulation Prototype.
Proceedings of the International Conference on Robotics and Automation, 2019

2018
Dynamics simulation for an upper-limb human-exoskeleton assistance system in a latent-space controlled tool manipulation task.
Proceedings of the 2018 IEEE International Conference on Simulation, 2018

Identification of Human Shoulder-Arm Kinematic and Muscular Synergies During Daily-Life Manipulation Tasks.
Proceedings of the 7th IEEE International Conference on Biomedical Robotics and Biomechatronics, 2018

2017
An Artificial Robot Nervous System To Teach Robots How To Feel Pain And Reflexively React To Potentially Damaging Contacts.
IEEE Robotics Autom. Lett., 2017


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