47 citations · 71 across the 14 of their papers we have counts for
14 papers
The Quadruped Soft Tail: Compliant Grasping and Swabbing for Contamination Surveys in Harsh Environments
Harald Minde Hansen, Nandita Gallacher, Kristin Y. Pettersen +2
Beryllium contamination surveys in radioactive areas are challenging for robots in environments cluttered with cables and electronics. To address this problem, we have developed a…
Tracking the Effective Surface Area of Non-Convex Satellites
Lauritz Rismark Fosso, Raymond Kristiansen, Jan Tommy Gravdahl +2
This paper presents a novel framework to track the effective surface area of non-convex satellites, enabling the use of aerodynamic drag in low Earth orbit for orbital control. The…
Data-Driven Dynamic Modeling of a Tendon-Actuated Continuum Robot
Harald Minde Hansen, Bjørn Kåre Sæbø, Kristin Y. Pettersen +2
Developing dynamic models for tendon-driven continuum robots is challenging due to their nonlinear, high-dimensional, and friction-dominated dynamics. This paper presents a compara…
Tendon-Actuated Robots with a Tapered, Flexible Polymer Backbone: Design, Fabrication, and Modeling
Harald Minde Hansen, Nandita Gallacher, Nicholas B. Andrews +3
This paper presents the design, modeling, and fabrication of 3D-printed, tendon-actuated continuum robots featuring a flexible, tapered backbone constructed from thermoplastic poly…
LeVERB: Humanoid Whole-Body Control with Latent Vision-Language Instruction
Haoru Xue, Xiaoyu Huang, Dantong Niu +8
Vision-language-action (VLA) models have demonstrated strong semantic understanding and zero-shot generalization, yet most existing systems assume an accurate low-level controller…
Deep active learning for nonlinear system identification
Erlend Torje Berg Lundby, Adil Rasheed, Ivar Johan Halvorsen +3
The exploding research interest for neural networks in modeling nonlinear dynamical systems is largely explained by the networks' capacity to model complex input-output relations d…
Sparse neural networks with skip-connections for identification of aluminum electrolysis cell
Erlend Torje Berg Lundby, Haakon Robinsson, Adil Rasheed +2
Neural networks are rapidly gaining interest in nonlinear system identification due to the model's ability to capture complex input-output relations directly from data. However, de…
Deep Model Predictive Variable Impedance Control
Akhil S Anand, Fares J. Abu-Dakka, Jan Tommy Gravdahl
The capability to adapt compliance by varying muscle stiffness is crucial for dexterous manipulation skills in humans. Incorporating compliance in robot motor control is crucial to…
A novel corrective-source term approach to modeling unknown physics in aluminum extraction process
Haakon Robinson, Erlend Lundby, Adil Rasheed +1
With the ever-increasing availability of data, there has been an explosion of interest in applying modern machine learning methods to fields such as modeling and control. However,…
Sparse deep neural networks for modeling aluminum electrolysis dynamics
Erlend Torje Berg Lundby, Adil Rasheed, Ivar Johan Halvorsen +1
Deep neural networks have become very popular in modeling complex nonlinear processes due to their extraordinary ability to fit arbitrary nonlinear functions from data with minimal…
CASCLIK: CasADi-Based Closed-Loop Inverse Kinematics
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. The module allows for combining multiple tasks that are resolved…
Merits of the Incremental Method for modeling Piecewise Linear functions
Mutaz Tuffaha, Jan Tommy Gravdahl
Several techniques were proposed to model the Piecewise linear (PWL) functions, including convex combination, incremental and multiple choice methods. Although the incremental meth…
On Model Predictive Path Following and Trajectory Tracking for Industrial Robots
Mathias Hauan Arbo, Esten Ingar Grøtli, Jan Tommy Gravdahl
In this article we show how the model predictive path following controller allows robotic manipulators to stop at obstructions in a way that model predictive trajectory tracking co…
Set-based Control for Autonomous Spray Painting
Signe Moe, Jan Tommy Gravdahl, Kristin Y. Pettersen
In this paper, a method is presented for lowering the energy consumption and/or increasing the speed of a standard manipulator spray painting a surface. The approach is based on th…