33 citations · 143 across the 18 of their papers we have counts for
8 papers · 1 filter
AutoGraph: Predicting Lane Graphs from Traffic Observations
Jannik Zürn, Ingmar Posner, Wolfram Burgard
Lane graph estimation is a long-standing problem in the context of autonomous driving. Previous works aimed at solving this problem by relying on large-scale, hand-annotated lane g…
Reward-Free Curricula for Training Robust World Models
Marc Rigter, Minqi Jiang, Ingmar Posner
There has been a recent surge of interest in developing generally-capable agents that can adapt to new tasks without additional training in the environment. Learning world models f…
You Only Look at One: Category-Level Object Representations for Pose Estimation From a Single Example
Walter Goodwin, Ioannis Havoutis, Ingmar Posner
In order to meaningfully interact with the world, robot manipulators must be able to interpret objects they encounter. A critical aspect of this interpretation is pose estimation:…
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…
Projections of Model Spaces for Latent Graph Inference
Haitz Sáez de Ocáriz Borde, Álvaro Arroyo, Ingmar Posner
Graph Neural Networks leverage the connectivity structure of graphs as an inductive bias. Latent graph inference focuses on learning an adequate graph structure to diffuse informat…
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…