41 citations · 42 across the 5 of their papers we have counts for
6 papers
Impedance Adaptation by Reinforcement Learning with Contact Dynamic Movement Primitives
Chunyang Chang, Kevin Haninger, Yunlei Shi +3
Dynamic movement primitives (DMPs) allow complex position trajectories to be efficiently demonstrated to a robot. In contact-rich tasks, where position trajectories alone may not b…
Flexure-based Environmental Compliance for High-speed Robotic Contact Tasks
Richard Hartisch, Kevin Haninger
The design of physical compliance -- its location, degree, and structure -- affects robot performance and robustness in contact-rich tasks. While compliance is often used in the ro…
Towards High-Payload Admittance Control for Manual Guidance with Environmental Contact
Kevin Haninger, Marcel Radke, Axel Vick +1
Force control enables hands-on teaching and physical collaboration, with the potential to improve ergonomics and flexibility of automation. Established methods for the design of co…
Minimum directed information: A design principle for compliant robots
Kevin Haninger
A robot's dynamics -- especially the degree and location of compliance -- can significantly affect performance and control complexity. Passive dynamics can be designed with good re…
Towards Learning Controllable Representations of Physical Systems
Kevin Haninger, Raul Vicente Garcia, Joerg Krueger
Learned representations of dynamical systems reduce dimensionality, potentially supporting downstream reinforcement learning (RL). However, no established methods predict a represe…
Safe rendering of high impedance on a series-elastic actuator with disturbance observer-based torque control
Kevin Haninger, Abner Asignacion, Sehoon Oh
An important performance metric for series-elastic actuators is the range of impedance which they can safely render. Advanced torque control, using techniques such as the disturban…