Author: Abu-Dakka Fares J.
Exploiting Object Physical Properties for Grasping
In robotic manipulation, robots are required to interact with, and adapt to, unknown environments and objects. In order to successfully accomplish these tasks, robots need to identify various properties of the objects to be handled. For these reasons, identifying object models that can represent the properties of objects has become a crucial issue in robotics. […]
Video on “Probabilistic Surface Friction Estimation Based on Visual and Haptic Measurements”
Watch the video demonstration of our latest paper on friction coefficient estimation
Master thesis on “Hybrid learning and control for human-robot interaction: an imitation learning perspective”
The goal of this project is to exploit more comprehensive information from humans, in order to learn as many skill patterns from humans as possible according to the tasks at hand.
Assignment on “Orientation Learning and Adaptation in Cartesian Space”
The goal of this assignment is to understand the KMP and to implement a C++ code for the kernelized treatment of orientation data in real setup.
Assignment on “Geometry-aware Dynamic Movement Primitives”
The goal of this assignment is to understand dynamic movement primitives in the context of geometry awareness and provide a C++ code for the algorithm.
Geometry-aware Dynamic Movement Primitives
Robotics Seminar Series. Third Session, Talk 2 – 13th March 2020. Speaker: Fares J. Abu-Dakka.
Accepted papers!!!
Great news!!! Our paper on “Geometry-aware Dynamic Movement Primitives” got accepted in ICRA2020