no code implementations • 5 Apr 2024 • Mads Erlend Bøe Lysø, Esten Ingar Grøtli, Kristin Ytterstad Pettersen
In this paper, we improve upon a method for optimal control of quadrupedal robots which utilizes a full-order model of the system.
no code implementations • 23 Mar 2022 • Mark Haring, Esten Ingar Grøtli, Signe Riemer-Sørensen, Katrine Seel, Kristian Gaustad Hanssen
Low complexity of a system model is essential for its use in real-time applications.
no code implementations • 19 Nov 2021 • Hossein Nejatbakhsh Esfahani, Behdad Aminian, Esten Ingar Grøtli, Sebastien Gros
The aim of this paper is to propose a high performance control approach for trajectory tracking of Autonomous Underwater Vehicles (AUVs).
no code implementations • L4DC 2020 • Signe Moe, Filippo Remonato, Esten Ingar Grøtli, Jan Tommy Gravdahl
Recurrent Neural Networks (RNNs) have a form of memory where the output from a node at one timestep is fed back as input the next timestep in addition to data from the previous layer.
1 code implementation • 20 Jan 2019 • Mathias Hauan Arbo, Esten Ingar Grøtli, Jan Tommy Gravdahl
A Python module for rapid prototyping of constraint-based closed-loop inverse kinematics controllers is presented.
Robotics
