activity
20182021
most citedDeep Reinforcement Learning Attitude Control of Fixed-Wing UAVs Using Proximal Policy Optimization

219 citations · 221 across the 3 of their papers we have counts for

collaborators

8 papers

eess.SY2021

Reinforcement Learning of the Prediction Horizon in Model Predictive Control

Eivind Bøhn, Sebastien Gros, Signe Moe +1

Model predictive control (MPC) is a powerful trajectory optimization control technique capable of controlling complex nonlinear systems while respecting system constraints and ensu…

eess.SY2020

Optimization of the Model Predictive Control Update Interval Using Reinforcement Learning

Eivind Bøhn, Sebastien Gros, Signe Moe +1

In control applications there is often a compromise that needs to be made with regards to the complexity and performance of the controller and the computational resources that are…

cs.LG2019

Accelerating Reinforcement Learning with Suboptimal Guidance

Eivind Bøhn, Signe Moe, Tor Arne Johansen

Reinforcement Learning in domains with sparse rewards is a difficult problem, and a large part of the training process is often spent searching the state space in a more or less ra…

cs.RO2019219 cited

Deep Reinforcement Learning Attitude Control of Fixed-Wing UAVs Using Proximal Policy Optimization

Eivind Bøhn, Erlend M. Coates, Signe Moe +1

Contemporary autopilot systems for unmanned aerial vehicles (UAVs) are far more limited in their flight envelope as compared to experienced human pilots, thereby restricting the co…

cs.RO20191 cited

Cooperative decentralized circumnavigation with application to algal bloom tracking

Joana Fonseca, Jieqiang Wei, Karl H. Johansson +1

Harmful algal blooms occur frequently and deteriorate water quality. A reliable method is proposed in this paper to track algal blooms using a set of autonomous surface robots. A s…

cs.RO20191 cited

Towards autonomous ocean observing systems using Miniature Underwater Gliders with UAV deployment and recovery capabilities

Erik Sollesnes, Ole Martin Brokstad, Rolf Klæboe +5

This paper presents preliminary results towards the development of an autonomous ocean observing system using Miniature Underwater Gliders (MUGs) that can operate with the support…