15 citations · 33 across the 6 of their papers we have counts for
6 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…
Task-Induced Representation Learning
Jun Yamada, Karl Pertsch, Anisha Gunjal +1
In this work, we evaluate the effectiveness of representation learning approaches for decision making in visually complex environments. Representation learning is essential for eff…
Motion Planner Augmented Reinforcement Learning for Robot Manipulation in Obstructed Environments
Jun Yamada, Youngwoon Lee, Gautam Salhotra +5
Deep reinforcement learning (RL) agents are able to learn contact-rich manipulation tasks by maximizing a reward signal, but require large amounts of experience, especially in envi…
Evolution of a Complex Predator-Prey Ecosystem on Large-scale Multi-Agent Deep Reinforcement Learning
Jun Yamada, John Shawe-Taylor, Zafeirios Fountas
Simulation of population dynamics is a central research theme in computational biology, which contributes to understanding the interactions between predators and preys. Conventiona…