Tønnes F. Nygaard — accepted AI-conference papers

2021

Semi-Supervised Gated Recurrent Neural Networks for Robotic Terrain Classification

Ahmadreza Ahmadi, Tønnes F. Nygaard, Navinda Kottege, David Howard, Nicolas Hudson

RA-L 2021

Legged robots are popular candidates for missions in challenging terrains due to their versatile locomotion strategies. Terrain classification is a key enabling technology for autonomous legged robots, allowing them to harness their innate flexibility to adapt to the demands of their operating envir

Cited by 17 Source ↗code ↗Scholar ↗

2019

Self-Modifying Morphology Experiments with DyRET: Dynamic Robot for Embodied Testing

Tønnes F. Nygaard, Charles P. Martin, Jim Torresen, Kyrre Glette

ICRA 2019poster

If robots are to become ubiquitous, they will need to be able to adapt to complex and dynamic environments. Robots that can adapt their bodies while deployed might be flexible and robust enough to meet this challenge. Previous work on dynamic robot morphology has focused on simulation, combining sim…

Cited by 32 Source ↗Scholar ↗