Plan-Conditioned Imitation for Robust Object Retrieval under Self-Occlusion in Dense Clutter

arXiv:2609.38857 · cs.RO · Submitted 2026-09-30 · Read on arXiv

cs.RO

Submitted: 2026-09-30

Updated: 2026-09-30

Project page: https://trace-retrieval.github.io

Terminology

• Trace — 38× in this paper · explained in 2 episodes
• Motion Primitives — 6× in this paper · explained in 2 episodes
• Aggregation — 5× in this paper · explained in 1 episode
• Digital Twin — 5× in this paper · explained in 5 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Action Space — 3× in this paper · explained in 1 episode
• Reinforcement Learning — 3× in this paper · explained in 4 episodes
• IEEE International Conference on Robotics and Automation — 2× in this paper
• Reward Shaping — 2× in this paper · explained in 2 episodes
• Self-Supervised Learning — 2× in this paper · explained in 8 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Covariate Shift — 1× in this paper · explained in 2 episodes
• Deep Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Distribution Shift — 1× in this paper · explained in 5 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Regret — 1× in this paper · explained in 3 episodes

Sources

• A Summary of Team MIT's Approach to the Amazon Picking Challenge 2015
• Proximal Policy Optimization Algorithms
• Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learning

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