28 citations · 85 across the 8 of their papers we have counts for
9 papers
RAMP: A Benchmark for Evaluating Robotic Assembly Manipulation and Planning
Jack Collins, Mark Robson, Jun Yamada +3
We introduce RAMP, an open-source robotics benchmark inspired by real-world industrial assembly tasks. RAMP consists of beams that a robot must assemble into specified goal configu…
Efficient Skill Acquisition for Complex Manipulation Tasks in Obstructed Environments
Jun Yamada, Jack Collins, Ingmar Posner
Data efficiency in robotic skill acquisition is crucial for operating robots in varied small-batch assembly settings. To operate in such environments, robots must have robust obsta…
Leveraging Scene Embeddings for Gradient-Based Motion Planning in Latent Space
Jun Yamada, Chia-Man Hung, Jack Collins +2
Motion planning framed as optimisation in structured latent spaces has recently emerged as competitive with traditional methods in terms of planning success while significantly out…
Follow the Gradient: Crossing the Reality Gap using Differentiable Physics (RealityGrad)
Jack Collins, Ross Brown, Jürgen Leitner +1
We propose a novel iterative approach for crossing the reality gap that utilises live robot rollouts and differentiable physics. Our method, RealityGrad, demonstrates for the first…
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…
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…