162 citations · 384 across the 14 of their papers we have counts for
5 papers · 1 filter
Semi-supervised Gated Recurrent Neural Networks for Robotic Terrain Classification
Ahmadreza Ahmadi, Tønnes Nygaard, Navinda Kottege +2
Legged robots are popular candidates for missions in challenging terrains due to the wide variety of locomotion strategies they can employ. Terrain classification is a key enabling…
Path Towards Multilevel Evolution of Robots
Shelvin Chand, David Howard
Multi-level evolution is a bottom-up robotic design paradigm which decomposes the design problem into layered sub-tasks that involve concurrent search for appropriate materials, co…
Real World Morphological Evolution is Feasible
Tonnes F. Nygaard, David Howard, Kyrre Glette
Evolutionary algorithms offer great promise for the automatic design of robot bodies, tailoring them to specific environments or tasks. Most research is done on simplified models o…
Traversing the Reality Gap via Simulator Tuning
Jack Collins, Ross Brown, Jurgen Leitner +1
The large demand for simulated data has made the reality gap a problem on the forefront of robotics. We propose a method to traverse the gap by tuning available simulation paramete…
Environmental Adaptation of Robot Morphology and Control through Real-world Evolution
Tønnes F. Nygaard, Charles P. Martin, David Howard +2
Robots operating in the real world will experience a range of different environments and tasks. It is essential for the robot to have the ability to adapt to its surroundings to wo…