most citedEvolving embodied intelligence from materials to machines

162 citations · 282 across the 5 of their papers we have counts for

collaborators

5 papers

cs.RO20209 cited

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…

cs.RO201928 cited

Benchmarking Simulated Robotic Manipulation through a Real World Dataset

Jack Collins, Jessie McVicar, David Wedlock +3

We present a benchmark to facilitate simulated manipulation; an attempt to overcome the obstacles of physical benchmarks through the distribution of a real world, ground truth data…

cs.NE201970 cited

Parameter Optimization and Learning in a Spiking Neural Network for UAV Obstacle Avoidance targeting Neuromorphic Processors

Llewyn Salt, David Howard, Giacomo Indiveri +1

The Lobula Giant Movement Detector (LGMD) is an identified neuron of the locust that detects looming objects and triggers the insect's escape responses. Understanding the neural pr…

cs.NE201913 cited

Evolving Spiking Neural Networks for Nonlinear Control Problems

Huanneng Qiu, Matthew Garratt, David Howard +1

Spiking Neural Networks are powerful computational modelling tools that have attracted much interest because of the bioinspired modelling of synaptic interactions between neurons.…

cs.RO2019162 cited

Evolving embodied intelligence from materials to machines

David Howard, Agoston E. Eiben, Danielle Frances Kennedy +3

Natural lifeforms specialise to their environmental niches across many levels; from low-level features such as DNA and proteins, through to higher-level artefacts including eyes, l…