SPN is a CNN that detects a spacecraft bounding box, classifies then regresses attitude, and optimizes position via Gauss-Newton, achieving degree-level attitude and cm-level position errors on real images after training only on synthetic data.
PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes
3 Pith papers cite this work. Polarity classification is still indexing.
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Robots detect underspecified reward features via demonstration variation and query targeted natural language explanations to improve reward recovery from imperfect demos.
Robots discover causal tool features through VLM suggestions and physics-based counterfactual perturbations in simulation, then transfer manipulation skills via conditioned keypoint matching.
citing papers explorer
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Robots That Know What to Ask: Recovering Misaligned Rewards through Targeted Explanations
Robots detect underspecified reward features via demonstration variation and query targeted natural language explanations to improve reward recovery from imperfect demos.
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Creative Robot Tool Use by Counterfactual Reasoning
Robots discover causal tool features through VLM suggestions and physics-based counterfactual perturbations in simulation, then transfer manipulation skills via conditioned keypoint matching.