From Rollout to Reset: A Graph-Based Harness for Autonomous Long-Horizon Manipulation Evaluation

arXiv:2609.19413 · cs.RO, cs.AI · Submitted 2026-09-16 · Read on arXiv

cs.RO, cs.AI

Submitted: 2026-09-16

Updated: 2026-09-16

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Verification — 17× in this paper · explained in 2 episodes
• Accuracy — 16× in this paper · explained in 1 episode
• Benchmark — 8× in this paper · explained in 2 episodes
• Point Clouds — 8× in this paper · explained in 2 episodes
• Foundation Model — 5× in this paper · explained in 3 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Foundation Models — 4× in this paper · explained in 7 episodes
• Compositional Generalization — 3× in this paper · explained in 4 episodes
• Generalization — 3× in this paper · explained in 13 episodes
• Graph Construction — 3× in this paper · explained in 3 episodes
• Vision-language models — 3× in this paper · explained in 2 episodes
• Benchmarking — 2× in this paper · explained in 3 episodes
• Conference on Robot Learning — 2× in this paper
• Diffusion Model — 2× in this paper · explained in 8 episodes
• Diffusion Models — 2× in this paper · explained in 6 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Grounding — 2× in this paper · explained in 3 episodes
• World Model — 2× in this paper · explained in 7 episodes
• Abstraction — 1× in this paper · explained in 1 episode
• Action-Conditioned World Model — 1× in this paper · explained in 1 episode
• Embodied AI — 1× in this paper · explained in 2 episodes
• Steering — 1× in this paper · explained in 2 episodes
• Task Planning — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• ${\pi}_{0.7}$: a Steerable Generalist Robotic Foundation Model with Emergent Capabilities
• Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning
• Native Video-Action Pretraining for Generalizable Robot Control
• Isaac Lab: A GPU-Accelerated Simulation Framework for Multi-Modal Robot Learning
• ManiSkill3: GPU Parallelized Robotics Simulation and Rendering for Generalizable Embodied AI
• robosuite: A Modular Simulation Framework and Benchmark for Robot Learning
• RoboDojo: A Unified Sim-and-Real Benchmark for Comprehensive Evaluation of Generalist Robot Manipulation Policies
• RobotArena $\infty$: Scalable Robot Benchmarking via Real-to-Sim Translation
• LiLo-VLA: Compositional Long-Horizon Manipulation via Linked Object-Centric Policies
• I-FailSense: Towards General Robotic Failure Detection with Vision-Language Models
• REPLAB: A Reproducible Low-Cost Arm Benchmark Platform for Robotic Learning
• RoboArena: Distributed Real-World Evaluation of Generalist Robot Policies
• ENPIRE: Agentic Robot Policy Self-Improvement in the Real World
• RADAR: Closed-Loop Robotic Data Generation via Semantic Planning and Autonomous Causal Environment Reset
• Zero2Skill: Bootstrapping Robot Skills through Autonomous Data Collection, Training, and Deployment
• Harness VLA: Steering Frozen VLAs into Reliable Manipulation Primitives via Memory-Guided Agents
• Scene Graph-Guided Proactive Replanning for Failure-Resilient Embodied Agent
• RoboTTT: Context Scaling for Robot Policies
• Foresight: Failure Detection for Long-Horizon Robotic Manipulation with Action-Conditioned World Model Latents
• Grounded SAM: Assembling Open-World Models for Diverse Visual Tasks

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• Fine-tuning is Not Enough: A Parallel Framework for Collaborative Imitation and Reinforcement Learning in End-to-end Autonomous Driving